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Many people prefer to purchase goods online for almost everything from groceries to clothing in the contemporary world. Compared to cash, it promotes online payments and becomes a reason for growth for the Buy Now Pay Later (BNPL) part of customer lending. It directs to short-term micro-credit options that allow consumers to shop online and pay within a few days or weeks with minor to no interest. Anyone can use this payment alternative on food delivery, travel booking, grocery, and some other platforms. Buy now, pay later services have been available in India for several years but have grabbed attention only in recent quarters as e-commerce and digital payments expand their reach. Klarna is one of the best BPNL startups of 2022 and has more than 100,000 users. It has become the second most valuable privately-owned FinTech in the world. The BNPL model has become more advanced due to technological innovation possible by the relatively recent maturity of artificial intelligence and machine learning. Apart from the top BPNL companies in India, traditional banks have also presented many offers to attract more customers. Following are the top BNPL companies in India. 1.ePayLater ePayLater is one of the top BPNL companies in India that was founded in 2015 and offered checkouts on online platforms without any problems. Customers can get an interest-free credit for two weeks. The startup is now looking to disburse the B2B and small-and-medium enterprises (SMEs) lending segment. 2. Simpl: Simpl is also one of the big BNPL players in India, founded in 2015, and has appeared as a significant challenger in the BNPL. It brings the comfort of online shopping. Its partners are famous online brands and offer their customers the ability to make purchases with one tap and pay later. People consider Simpl’s solution a critical factor in accelerating the adoption of digital payments in e-commerce that significantly enhances the consumer experience. 3.LazyPay It also includes in top BNPL companies in India. People who use it can shop online with one tap and pay later within 15 days, or they can also convert them into equated monthly installments (EMIs). This startup also gives loan options. LazyPay is functional on many websites in India. This startup presents paperless credit disbursal with minimal documentation. 4. Amazon Pay Later It is also a top BNPL company in India that is a unique and convenient option for making payments that enables its customers to extend their access to credit. Amazon will offer an instant credit line to customers to purchase goods and pay their monthly utility bills. Buyers will get access to instant credit that they can use to buy any product. Amazon Pay Later service offers the option to repay in the following month without any additional fees or in easy EMIs up to 12 months at nominal interest rates. Further, such startups also utilize artificial intelligence to get access to customers. 5.ZestMoney ZestMoney is one of the top BNPL companies in India that was founded in 2016 delivers fast. It is reliable and affordable EMI services across the country. Its users can shop online and pay back later with easy installments. The startup’s platform utilizes mobile technology, digital banking, and artificial intelligence (AI) to access people. The financial institution or payment industry that uses artificial intelligence can process real-time transactions. India has a massive population with low income and poor or non-existent credit histories. It makes it problematic for them to qualify for credit by traditional channels. ZestMoney enables more people to get credit. Then, they can participate in the consumer economy. In return, it grows the digital footprint. 6. Flipkart Pay Later Flipkart Pay Later offers credit solutions to customers and claims to provide bank-grade security without an OTP for most transactions. It has the option to make partial repayment of bills. Its users can pay a minimum due amount, which a convenience fee retains at first. Many Indians do not have access to credit cards. Hence, customers do not get access to short-term credit to make purchases. So, Flipkart Pay Later is helpful for those consumers to buy essentials. 7. Paytm Postpaid In 2019, payments giant Paytm was also included in the BNPL segment with its Postpaid services. Bills are paid on the 1st of every month and can pay till the 7th. It indicates a relatively longer-term credit offering than other BNPL players in India. However, unlike other BNPL players, Paytm charges a convenience fee of zero to 3% of net monthly spending. 8. Flexmoney Flexmoney is a BNPL player in India, and it is a full-lifecycle digital credit network for lenders and merchants to offer frictionless. It also secures checkout finance and offers flexible payment options like LazyPay, where consumers can select between full payment and EMIs. However, this setup does not give financing from its pocket. It simply helps lenders reach a wider audience and tap into the BNPL market by connecting them with online merchants. 9. OlaMoney Postpaid OlaMoney Postpaid is one of the easiest ways to pay for your different online services. OlaMoney Postpaid ensures payments without you worrying about wallet recharge. Users can use this service for up to 15/30 days, depending on your billing cycle. It also delivers standard features such as interest-free credit with 15-days repayment. 10. Capital Float It is a well-known BNPL player in India that gives digital credit to individuals for their personal and business loans to small and medium enterprises at interest rates. Capital Float functions as a FinTech lender company. BNPL startups rise due to their various benefits. For instance, it saves time because customers can spend money to purchase what they want despite waiting for the next salary. Furthermore, people do not have to worry about paying heavy interest rates or other costly repayments. Synergy Labs is an Artificial Intelligence and Machine learning solutions provider that concentrates on developing enterprise-grade solutions for FinTech startups. It was established in 2017. It helps FinTech startups accelerate growth with stable and scalable solutions. Synergy Labs provide full assistance to its customers regarding its better usage. If you are a startup or an enterprise in FinTech that is looking to develop new-age solutions drop us an email at info@synlabs.io to know more about what we can do for you.

Over the past few years, where the global economy nosedived because of COVID-19, a business has made tremendous strides in terms of market cap growth and the return on investment opportunity it ensures. The Peer-to-Peer (P2P) Lending business provides a 12-14 percent return on average. According to data from P2P lending site LenDenclub, 4,50,000 new lenders joined the network in FY21, compared to 50,000 at the end of FY20. With this, the total number of registered lenders on its platform surpassed 5 lakh, a 900 percent increase in a year. At the end of FY21, Faircent, India's first P2P lending platform to be granted an NBFC-P2P license by the RBI, had 2 lakh lenders. In FY21, the platform disbursed Rs 1,145 crore in loans, up from Rs 920 crore in FY20, a 24 percent increase. As of today, the overall loan book stands at Rs 2,250 crore. India's FinTech industry, according to Boston Consulting Group, is on the verge of enormous profit maximization. By 2025, the industry is anticipated to be worth USD 150-160 billion. So, what exactly is this peer-to-peer (P2P) industry, and why is it so profitable? Peer-to-Peer (P2P) Lending The crowd-funding model underpins the peer-to-peer lending paradigm. Peer-to-peer (P2P) lending allows individuals to obtain loans directly from other individuals, avoiding the financial institution as a middleman. Due to websites that make it easier for consumers to conduct P2P lending, it has gained traction. Peer-to-peer lending has been nicknamed "Social lending" or "crowdlending". Why P2P? Borrowers who use peer-to-peer (P2P) lending can get loans at cheaper interest rates than they would get from traditional lenders like financial institutions and banks. Most financial service providers do not charge any fees when investors offer money to borrowers directly through a P2P platform. Thus, both parties benefit from this model. Top P2P Companies in India Let's have a look at the top P2P companies in India and assess their performance and prospects for growth. Lendbox Lendbox is one of India's most popular peer-to-peer lending websites. Headquartered in New Delhi, Lendbox is an RBI-certified Non-Banking Financial Company-P2P organization founded in 2015. With roughly 50,000 registered investors and 2,00,000 registered borrowers, it has enabled investors to achieve previously unheard-of profits. Lendbox intends to revolutionize the personal loan sector in India with a team of young and energetic experts that have joined together from various backgrounds. With an average return of 24 percent, it is an effective tool for multiplying your money and establishing a steady passive income. Faircent Faircent is among the oldest P2P players in India. It was the first peer-to-peer (P2P) lending platform in India to get a Certificate of Registration from the Reserve Bank of India as an NBFC-P2P. Faircent is a Gurugram-based P2P lending network launched in 2013 by Rajat Gandhi, Nitin Gupta, and Vinay Mathews. Faircent.com has a vast marketplace of over 1.5 lakh lenders to meet the funding needs of credit-worthy borrowers. Faircent introduced Anti Lockdown Loans in April 2020. It was a unique loan product designed to help businesses stay afloat during the Coronavirus pandemic. Lendingkart Lendingkart is one of the leading AI-based FinTech startups. It employs Artificial Intelligence (AI) technology to efficiently and precisely assess creditworthiness to connect borrowers with lenders. Lendingkart is a FinTech startup based in Ahmedabad that was launched in 2014 by Harshvardhan Lunia and Mukul Sachan. This fintech firm strives to make credit more accessible to people and small and medium-sized enterprises. The company operates and provides services in over 4000 cities across India, helping over 1,50,000 businesses. LenDenClub LenDenClub is among the fastest-growing P2P players in India. LenDenClub is a Mumbai-based peer-to-peer lending company started in 2015 by Bhavin Patel and Dipesh Karki. It is a technology-driven platform that allows borrowers to connect directly with lenders, bypassing intermediaries and lowering expenses. Having more than 10 lakh investors, the organization has disbursed loans worth roughly ₹2000 crores to more than 25 lakh borrowers. You may expect a per annum return on investment of 12% with LenDenClub. RupeeCircle RupeeCircle can be categorized as a highly successful AI-based FinTech startup. Ajit Kumar, Abhishek Gandhi, Ashish Mehta, and Piyush Saurabh launched RupeeCircle, a Mumbai-based financial firm, in January 2018. In comparison to traditional financial institutions, it uses cutting-edge technology to offer lower interest rates on loans. By eliminating intermediaries, it also delivers larger profits to lenders. RupeeCircle has disbursed loans worth ₹ 34.7 crores to 1.7 lakh registered users. The average per annum returns on investment stand at 24%. Capital Float Capital Float is India's leading Buy Now Pay Later and credit marketplace, catering to both salaried and self-employed individuals. It was founded in 2013 by Gaurav Hinduja and Sashank Rishyasringa. It is an AI-based FinTech startup that blends AI technologies with human experience to make risk assessment and marketing easier. Capital Float is certainly working towards being the top P2P company in India. To better target clients, Capital Float deployed AI models in its marketing initiatives. They bought Walnut, a popular personal finance management software, in 2018, which propelled them even further into the credit-solutions market. Personal lending (through Walnut), business financing (including short-term loans for small businesses), and their Buy Now Pay Later platform are currently offered by Capital Float. Future for FinTech and P2P companies in India The Indian FinTech scene has been irrevocably transformed by peer-to-peer (P2P) lending. Every Indian now has easy access to immediate finance. As a result, India is rapidly becoming a credit-inclusive nation, while also providing investors with one of the most promising asset classes. In this regard, of all the recent FinTech disruptors, peer-to-peer lending is by far the most inventive. The rate of expansion of top P2P companies in India is increasing competition and creating new and improved standards. Peer-to-peer lending's success will inevitably leave its competitors obsolete. If you want to navigate the FinTech industry and want FinTech solutions for your startup, visit synlabs.io SynergyLabs is a cutting-edge technology consulting firm that specializes in the development of enterprise-grade solutions, including ready-to-deploy PODs for fintech startups. Founded in 2017, it is a well-funded firm assisting FinTech companies in accelerating their growth by providing solid and scalable solutions. It offers services in BFSI (Banking, Finance, and Insurance), logistics, retail, and telecom. If you are a startup or an enterprise in FinTech that is looking to develop new-age solutions drop us an email at info@synlabs.io to know more about what we can do for you.

There are many, I mean millions and millions, of images and videos out there! You’ll need a great combination of computer vision models in order to drive value from them. Each industry is different that’s why having an experienced and knowledgeable partner is always a must. You’ll need a development and design partner that will understand your business and what it stands for. Find a company like SynergyLabs! Founded in 2017, our company has been one of the best tech partners for companies that are looking to elevate their business to the next level. We offer services that can radically change your business process and more! From development, design, AI, and DevOps, you can count on us to bring knowledge and experience to the table. We’ve been proud of all the projects and relationships we managed to build in the past. Today, we want to highlight the latest collaboration that was featured on Clutch. Clutch, for those that don’t know, is hugely respected within the B2B space for connecting small, mid-market, and enterprise businesses with service providers that fit their needs. An AI Saas provider hired our team at first to build computer vision models based on Python and other similar technologies. After that, our team helped in speeding up the client’s transformation and creation of new features that were necessary for their customers. Today, we are building a couple of crucial components that didn’t exist in our earlier setups. To share their experience with working with us here is an associate for the AI SaaS company: “As we’re a startup, we can’t invest a lot of money in a solution. Considering this situation, SynergyLabs has helped me develop market-ready MVP solutions that we can take to market. If people like them, we then develop complete solutions. They’ve been really helpful in this regard.” The client was impressed with the attentiveness that we displayed throughout the project. They also appreciated the fact that our team could create and develop the solutions that were needed very quickly. Apart from Clutch, you can also check us out as a leading company on Top Artificial Intelligence firm’s website. Top Artificial Intelligence is a top resource for buyers looking to find top designers, marketing companies, and developers that specialize in various industries. Let’s turn your ideas into realities! Our team is always ready to take on new challenges and help your business grow. Give us a call today and let’s talk about our business!

Overview An autonomous driving technology company in the US wanted to optimize their vehicle performance at an optimal level and the best way they could find through digitizing their operation patterns using autonomous technology. However, they looked beyond typical Automated Driving Assistance System or ADAS technology. They wanted their vehicles to drive the longest miles on the road. They thought it could help them heighten the driving experience by simulating data while also focusing on building cost-effective and efficient transportation for their business growth. In their mission, as they joined forces with SYNERGYLABS, our synthetic datasets efficiently trained AI models to help their vehicles achieve accuracy and enhance autonomous driving in real-world scenarios. About the autonomous driving technology company The client established a trusted autonomous driving technology company in North Carolina, US. With more than 2 years into the operations of building autonomous driving technology, they have clients from top locations in the US, and they are home to more than 10k reliable clients. Their technologies are highly preferred for business across retails, manufacturing, fashion, and more. They are growing from a team of ten members to 80 members now with the increasing operating pressure, which needs to ensure high performance and efficiency for their users. The ease of use is highly expected to make returning to the parking lot or safety easily achievable. The regular market demand for products urges them to implement autonomous driving technology for efficiency, lower risk of collisions, and high performance for their users. The Challenges Autonomous vehicles are doing rounds for a long time now with AI-based drones delivering cargo at doorstep or ride-hailing services making riding more efficient and easier for users. Although LiDAR or RADAR sensors make building autonomous vehicles apparently purposeful, a deep level application of these technologies proves effective when they help with simulation and encourage a safer and more productive future for riders any autonomous vehicle companies. The client understood the pressing needs of building algorithms using massive datasets or by generating synthetic data in the real world. They needed these massive synthetic datasets to help with training models that blend closely with related scenarios and enable friction-free autonomous driving. The purpose behind harnessing synthetic data and using them to build AI models was to detect real-world situations in real-time more accurately. They seek the level of accuracy or expertise to generate synthetic data and integrate it into the ADAS technology so as to nurture their autonomous vehicle goals more effectively. As ADAS and its features also aim at making autonomous driving environments easier and efficient, they still lack capabilities to offer accuracy and precision with data detection. To help with harvesting data and building synthetic datasets, it needs extensive expertise and experience across the Artificial Intelligence, that supports the development of AI models to be properly trained and programmed to aid in autonomous driving solutions. They wanted to collaborate with leading AI consulting partner with strong industry experience and a detailed orientation to AI tools and technologies. They turned to SYNERGYLABS to help them train modern deep neural networks using synthetic data and build advanced AI data models to work in the most critical road situations. The Solutions SYNERGYLABS’ built synthetic data provided the best template to build AI-based autonomous security systems that easily sync with ADAS tools and most significant features like radar sensors, LiDAR units, and cameras. Accurate detection of different real-world scenarios Our synthetic data-based platform is programmed to simulate off-road and on-road traffic scenarios. Additionally, pixel-perfect annotated training data is capable of delivering accuracy through simulation of multiple scenarios and empowers their vehicles to be able to identify and overcome different perception issues. The autonomous capability that we built for their vehicles through synthetic data generation gives their drivers the ability to drive safely by avoiding the toughest terrain, having better cruise control with accurate path and space judgment, and also escaping blind spots. Increasing the ability to be trained with synthetic data By helping train the decision-making and recognition algorithms of their AI models to be built into autonomous technologies like ADAS or other features, we prepare accurate datasets. The raw images the vehicles capture pertain to different sets of objects like traffic lights, moving vehicles, people, and road signs are some of the critical things the AV needs to recognize. We harness raw data and use bounding boxes and labels to infuse them back to AI models. By analyzing and detecting thousands of raw images and other key data, AV gains insights into recognizing the objects and improves comprehension to respond accurately to the evolving scenarios. As they used synthetic data for AI-models, they were able to maximize the power of autonomous vehicles and developed unique features to detect the drivable path or passable area without creating any threat opportunity for the nearby objects like cyclists, pedestrians, or other vehicles. A high-quality data annotation makes it easier for them to train their AI models and encourages the development of safer autonomous vehicles. Different variables to train with synthetic data We generate synthetic data to recognize billions of data around the driving pathway. They include- Variable weather Poor lighting Different types of road markings, blind spots Passable or driving conditions Infrastructure asset Full suite of libraries of pedestrians, vehicles, and cyclists Traffic signs across the world Parking lots or parking systems The Results Our end-to-end synthetic data platform provides better simulation for ADAS technologies, which elevated our clients’ expectations to build a safer and cost-effective driving experience for users. From training to testing to deployment, our AI-powered technologies delivered the best results with precision, which made their investment into synthetic data generation purposeful and efficient at the same time. Technology Used Computer vision, AI, synthetic data, Ext JS, HTML, Java, Springboot, MySQL, Postgres, Socket programming with netty and Tensor Flow, python.

Overview With a vision to infuse enhanced self-driving capabilities into its automobiles, our client wanted to prevent front-end collisions en route to its locations and bring efficiency to its manufacturing portfolio. Utilizing SYNERGYLABS’ designed computer-vision-based advanced driver assistance system or ADAS, the automobile manufacturer in India prevented service delays, reduced the number of collisions, for users while also improving customer satisfaction. About the Automobile Manufacturer Company Our client- a renowned automobile manufacturer company had a number of plants to manufacture the best-designed vehicles for their customers. They are responsible to bring out in the market the best model with high performance and efficiency to help run for the longest miles and deliver optimal services that aptly meet customer demands. Their long-industry reputation has been built around their efficiency in encouraging productivity in all sectors they serve without disrupting operational efficiency. To match the customer expectations, they leverage speed and performance through digitization. And, now, they are looking to maintain long-term customer relationships to grow and scale beyond the known boundaries and territories. The challenge After the expansion of their customers, they started feeling growing pains. Their vehicles sweep through highways, roads, and lanes, increasing the rate of long-haul transit for their users occasionally or frequently. They felt a growing pressure to keep up with vehicle and asset maintenance and give the best value to their users. This requires users to improve concentration on the highways or spaces where they drive to keep a safe distance from the vehicles ahead of them. Moving along the highways for a stretch of 4 or 6 hours- if not 8 hours is many a time usually a stressful journey for drivers. Simultaneously, they also need to keep pace with how safe their vehicles can move along the road. The approach is to determine that their vehicles are resulting in fewer risks associated with highway collisions due to drivers’ negligence or inadvertent driving faults. With the safety and security of public commuters in mind, they are committed to encouraging safety, eliminating the chances of injury or accident-related losses, and building a secure driving experience for all. “Over a few years, we’ve observed that our automobiles need more enhanced technology beyond GPS tracking systems not just to help us with tracking of vehicles and communications. We needed technologies that bring the convenience of managing our automobiles and also safety’, Vice President at the automobile manufacturing company. For the owner, making their vehicles comply with road safety, efficiency, and growth strategy was challenging. They looked for support that could allow them to meet the immediate needs of customer satisfaction and scalability in the ever-evolving atmosphere. The Solutions Our team at SYNERGYLABS proposed a computer vision-based front-end collision avoidance system. This machine learning-programed system gives the best solution to transform the under-the-hood driving experience for every user. We built dual-facing cameras programmed with computer vision (machine learning/natural language processing) technology to put them under the hood or driver cabin. Synced with a touchscreen dashboard, SYNERGYLABS-programmed predictive collision system provides real-time critical threat alerts on the screen to alert drivers and help take control of the vehicle before the incident could pose a huge risk to their assets and people. To help them continuously monitor real-time driving situations and improve driving behavior, we gave our client the best solutions to help with identifying potential hazards and avoid them in real-time. Avoiding unpredictable risks as the vehicles move along the road becomes possible by using AI algorithms that simplify the assessment of situational risks. With this, the system helps the owner determine the severity of the disruption or distraction on the road ahead- the nearly running traffic, stoppage, and the nearby locations. By continuously fetching risk data that deliver real-time feed on the screen of the anti-collision system dashboard, some critical variables like driver behavior, vehicle movement, and level of collision are fast to grasp and comprehend. Thanks to the Convolution Neural Network or AI-based model that we built to infuse into the system and program to detect what threat the vehicle is likely to experience and alert the driver to handle the risk much before it could turn into a huge risk and impact their operations. The predictive collision system we built for the client features critical components to enhance every step of the driving journey. Headway collision monitoring - In critical weather conditions- heavy snowfall, cyclones, rains, or floods- taking control on speed control is tough for drivers. Our dashboard gives an alert when the vehicles come too close that may be a significant reason to cause rear-end or front-end collisions. The fleet drivers therefore can avoid collisions when the distance between two vehicles becomes unsafe. Lane departure warning - The run-off-road crashes occur when unintended lane departure happens. Our predictive collision system can easily help drivers maintain lane marking with visual and audio signals as they deviate from the lane. Drivers now can maximize our computer-vision-based built AI model that helps them reduce serious injuries and also serious fatalities on road. Obstacle detection - The front cameras use sensors to detect objects through the driveway. Usually, drivers can’t recognize obstacles and maintain the right distance while driving during low-visibility critical weather conditions like rain, snow, and fog. The collision avoidance system also put together the best of components that include adaptive cruise control, emergency brake assist, and speed limit indicator. “We evaluated a number of on-the-shelf predictive collision products before we zeroed in on SYNERGYLABS. They understood our needs better and offered us the most sophisticated AI-powered technology to maximize the power of automotive autonomy and support our commitment to safe driving”, the owner of the manufacturing company. The results There’s a visible increase in safety through enhanced monitoring of driver behavior. Front-end collisions are less likely to happen- they are building happy customers who are fond of autonomous driving technology. They were also satisfied by giving their clients the ability to reduce the number of visits to the repair shops. Technology used Computer Vision, AI, Ext JS, HTML, Java, Springboot, MySQL, Postgres, Socket programming with netty and Tensor Flow, python.

Overview Realizing the need for transformation of the under-the-hood cockpit applications in today’s vehicles, this Wales-based mobility solutions provider emphasized employing advanced in-vehicle infotainment features to build customer interest and increase sales. As SynergyLabs stepped in to build better connectivity, provide driving comfort with enhanced mobility, our client successfully built the solutions as expected. Our Android technology-powered key in-vehicle solutions to meet consumer demands and promised to support future innovation that enhances autonomous capabilities in vehicle cock-pit and meets complex requirements of autonomous automotive technologies. About The Automaker With an increasingly growing demand for autonomous mobility solutions, this UK-based automaker emerged with a vision to develop head-up displays, cockpit navigation supplies, and original equipment manufacturers. At the same time, the infotainment solutions scale in-vehicle driving experience. Their solutions are aimed at making virtual driving safe and secure while enabling a more carefree and enjoyable driving and riding experience for drivers and passengers respectively. Beyond improving the driving experience with efficient navigation that tells about the safe maneuver on the road ahead, they are envisioning to amp autonomous driving capabilities. By allowing everyone in the move to get informed about the vehicle behavior in line with the surroundings, it comprehensively encourages safety and security for the users. More than three years into the development of head-up display systems for the automotive industry, they gain a lot of traction in the automotive market and have built lasting relationships with the leading automakers. The challenges Usually, an infotainment automotive display or head up display that sits in the vehicle cockpit provides interactivity to the users to allow internal vehicle status to the users. The infotainment windshield has to deliver beyond the usual features of music or other entertainment content, it must supply vehicle status information and navigation support. ‘Everything needed a change with our existing infotainment system to be able to work as user expectations. We required some more robust features to allow for added functionalities and performance to interpret what drivers can see on the head-up displays or windshield dashboard or infotainment system. So, we could provide our users or drivers frictionless driving experience and safety, said a chief architect at the automotive company. To embed all of these features all together into the windshield dashboard, the client wanted a solution that flexibly provides their users with essential vehicle interaction through touchscreens, voice and gesture recognition, and steering controls. But, combining all these essential features into one system requires intense expertise to put through a high level of integrations by following a lot of toughened variables. The Solutions As SynergyLabs looked to build an infotainment system, the first technology we chose for the purpose was the Android operating system. The technology gives more control over how drivers want to maneuver their vehicles with inputs from real-time motion feeds. Built-in Google Maps and Android Voice recognition could combine together to create a whole new driving experience for users. Infotainment dashboard design We put the best features together to give our clients exactly what they needed to build for their head-up display systems and transform user interactivity. It highly meant to provide high-caliber functionalities relating to gathering weather information, routing vehicle paths to the right direction using the best support from map-based navigation. Our team of engineers designed a few of the crucial parts of the infotainment system using the following tools and technologies- We used an Android KitKat-run processor to support this interactive dashboard. It included power storage supported by DDR and eMMC/NAND memory chip. Also, we built multimedia components, a display screen or interactive user interface, and a reverse camera. We enabled the communication connectivity using low latency or BlueTooth technology to allow data transfer and faster communication using WiFi technology. Google Maps as an efficient tool to use Android location manager was designed to seamlessly integrate with GPS and provide location information on the dashboard. The head-up display also included a Tyre Pressure Management tool to collect tire pressure in real-time. The system use cases For ease of use and easy understanding of the whole procedure, we built one app to be easily accessible through the Android app. It was designed to save time and improve the usability of the infotainment processes. Keeping user experience in mind, restricts time being spent in the vehicle cockpit to understand how system procedure works. Going forward, the Android Infotainment system provided more than just a graphic display. Our solution captures real-time information from vehicle cameras and sensors embedded in the car. By pulling data that visualizes the current wheel pressures in graphical format or GPS data that gives insights into the road pattern itself for better navigation. GPS-enabled navigation warning gives better autonomous capabilities to maneuver the vehicle in the right direction without inviting any accidental risks on the road. Before we put our infotainment system out for customer use, we went through a lot of iteration and test its usability for accuracy and performance. ‘SynergyLabs Android-based infotainment system or head-up display was rightly optimized to what our modern consumers are expecting from hi-tech vehicles with all possibilities of autonomous features that ensure comfort and convenience. We are delighted the system now would help us scale with the growing changes in the mobility world with a little upgrade to initiate,’ said the CTO at the company. Technology Used Android operating system, computer vision, Ext JS, HTML, Java, Springboot, MySQL, Postgres, Socket programming with netty and Tensor Flow, python.

Since the first outbreak of Coronavirus (COVID-19) in Wuhan, China, the strain is stronger than ever now changing its mechanisms by the day and even by the hours. It is deadlier than seasonal influenza or what we know about SARS and MERS, which has recorded about 3.4% death cases globally so far as per the World Health Organization. Having spread across at least 100 countries, COVID-19 has turned out to be a growing global public health emergency. Not only does it threaten lives, but it is affecting businesses, ruining the travel across the world and raising anxieties over the global economy. Despite having similarities with seasonal influenza, COVID-19 has some ambiguous properties with relatively new features preventing scientists from discovering a specific treatment or a vaccine. Also, it is as transmissible as influenza. As it is evolving, immunity is not so strong to avoid its risks, putting the entire human population to COVID-19 infection threats. Amid this global crisis, where even the slightest contact to the virus proves to be the deadliest, Artificial Intelligence reinvents the global efforts in curbing the further health risks by the pandemics. AI Fights with Coronavirus We have already witnessed how quickly China has enabled faster and better response to this epidemic with the effective application of AI. They have brought to the rescue a range of Artificial Intelligence-equipped tools such as disinfecting robots, drones powered by thermal cameras, smart helmets, and facial recognition-based software suites. But, how do these so common technologies like Machine Learning and Artificial Intelligence provide excellent assistance in the battle of disease prevention? Artificial Intelligence expanding its capabilities with new dimensions to sustainability Big data analytics is the step towards implementing the right strategy for the prevention of further disease transmission, which Machine learning and Artificial Intelligence can work with. Discovering vaccines, treatments, and cures It is not unknown that COVID-19 has no specific treatment and vaccines. But unlike the SARS outbreak that took more than a year to develop the right cures through clinical trials, by which point the pandemic came to end, AI seems to provide with some breakthrough in R&D for the discovery of effective treatments. A deep insight into the patterns of COVID-19 is enabled using advanced AI techniques. This process helps analyze the genetic makeup against the already known virus mechanisms speeding up the research outcomes. Also, it is reported that an analysis could be made faster. One such instance reflected an analysis of the coronavirus RNA which was reduced from 55 minutes to 27 seconds. What does it mean? This AI-based analysis can lead to a rapid quarantine process through effective isolation. Genetic sequencing is a critical part of understanding the mutations of the original virus prompting for continuous testing which is time-consuming. The computational power of AI is used to create vaccines through generating information involving genetic sequencing which is fast and accurate to obtain the right virus sample without spending much on the logistics costs. This could be another positive side to AI that gives confidence to several clinical libraries to roll out vaccines for clinical trials shortly. Given trials, some challenges are likely in the forms of lack of resources and effective coordination to deploy the doses across the needy locations. For now, curbing transmission through containment as much as possible appears effective Big data analytics for containment To protect the public health from the threats of coronavirus, AI and data analytics can be leveraged to gain access to early signs that would probably point at the possible outbreak of the epidemic. Using the sophisticated AI tools and techniques, we can mobilize and put into use some specific strategies to identify, allocate resource and contain a week earlier than the officials could alert and stop it from spreading. These predetermined actions are more robust in combating a large-scale epidemic. The government health insurance database is the most reliable source for harnessing essential data, which can be overlaid with immigration and customs databases and a robust data analytics platform can be orchestrated. More so, we can derive information from different sources, e.g. clinical emergency data, flight records, social media, physicians’ records, and not to mention the sales records of anti-fever medication. AI experts must adhere to the changing patterns of the events as to how they appear in a specific epidemiological outbreak and observe to find rare but meaningful traces of events such as glaring absenteeism from school in a certain area. For case identification, big data analytics provides real-time alerts as early as it detects clinical symptoms and travel records during a medical visit. Novel technologies such as QR code tracking feature and online reporting of travel history may provide a new dimension to detect health risks of the travelers in the last 14 days amid the coronavirus crisis. Thereby, availing these reports much earlier can help health care systems or the government improve the scopes for effective quarantine procedures for patients or have an adequate supply of antiviral medications or materials. For limiting the disease further, AI can provide an opportunity to predict the next probable outbreaks with a new virus by allowing scanning high traffic areas like the food market. Taiwan has been successful so far in controlling the spread of COVID-19 by following active methods of big data analytics. Despite being 81 miles away from China and extremely high-risk, the country recorded 49 COVID-19 cases with only one death. Other countries too should establish a data analytics-based public health response mechanism to enable rapid action in battling the virus outbreak. AI for quarantine Policymakers can’t put patients into quarantine whenever they want to. Because it can result in disruptive consequences and contribute to negative long-term effects. Hence, health care systems must know when and how they need to isolate people. Syndromic Surveillance can be put into use to relay information outside of a clinical belt about the possible disease risks. By enabling statistical analysis using text mining and natural language processing, AI can watch activities on social media to corroborate data that could hint about patterns found in coronaviruses. Thereby, the combined efforts of syndromic surveillance and social media analytics help analyze rare events from different data sources and ease the investigation, speeding up the process of efficient and effective quarantine process. Disease detection at hospitals and outside For AI firms, this is not an opportunity to scale as AI leaders, but an utmost responsibility to extend help in tackling 2019- nCov. Facial recognition cameras can be upgraded with technologies to scan crowds for symptoms and identify people not wearing masks. Deployed across schools, stations, and community centers, AI-enabled tools can identify faces covered with masks without tampering with its accuracy level. Using a thermal sensor embedded on the smartphone, a real-time temperature can be measured in the public place. A similar feat can be achieved using an infrared sensor in combination with AI technology and computer vision that can detect individuals up to 200 in a crowded place and an alert can be sent to authorities when it detects temperature above 37.3 degrees Celsius since it is the first sign of coronavirus. Deep learning models reduce the time for CT scan reports and show performance enhancement for radiologists. Thus, it holds the potential for encouraging early disease diagnosis, isolation and limiting the epidemic. Since it is highly transmissible, AI can help in automating tasks for nurses and physicians. The capability of these systems including chatbots can generate an accurate report during a survey for detecting citizens for symptoms. The wrap-up AI drives decisions. And with data-driven decisions, we can act fast and smart by taking up immediate steps to prevent the coronavirus from spreading further. Irrational behavior and panic are most likely during an epidemic. But policy should be made to educate people through constant research and development. So, we need to remain vigilant while investing in new vaccine technologies to create a robust health care system. In the pursuit of this achievement, AI-powered solutions can help.

We have now got beyond the phase of AI development. It is now time for building strategies to implement this unique and smart tool to achieve unprecedented accomplishments. Although this advanced technology is everywhere, we are more than unwilling to leverage its capabilities. Let’s delve deep to find out some dynamic and robust caliber of AI that can change your perspective. Here are 4 unique use cases of specialized fields of AI that are unique and novel in its approach. Crowd-Sourced Market Research Crowdsourcing, the idea behind this novel approach is to incentivize crowds to offer their insights or generate ideas about some matters and facilitate better solutions to a problem. Even though some setbacks were there at the initial stage, crowdsourcing is accepted as the most preferred method for market research. Thanks to the convergence with AI. Today, it is estimated to be valued at $6.5 billion. All this is to ideate new phenomena for bringing machine and human intelligence together that could offer intelligence analysis of crowdsourced discourse referring to “who says what and why?”. So, the aggregate knowledge of communities and insights from discourse analysis may foster knowledge development with the help of advanced machine learning capabilities. Also, the crowd-based source enables the development of improved knowledge platforms with real-time graphical representations, patterns, and insights that improves prediction capabilities. The primary objective of the AI-based crowdsourced market research is to converge with machines and swarm intelligence to derive essential insights for optimized solutions. Benefits When machine learning and human judgment combine, AI tools derive human inputs by monitoring its behavior and correcting their actions. This capability helps better decision making during critical events. One example is the Artificial Intelligence for Disaster Response (AIDR). This uses insights from crowdsourcing and offers real-time disaster prevention methods to address the situations. AI with crowdsourcing capabilities can identify patterns and metrics of images or videos with human inputs. This results in the accurate processing of data and offers better knowledge development. It is capable of offering crowd knowledge through graphs or textual based arguments and raising questions on issues. This is a phenomenon that visualizes data with artificial intelligence. A human-machine interface target to improve understanding patterns of geopolitical events and suggests forecasting to improve the event. It accelerates data collection and faster development of models. It enables faster onboarding of contributors and optimization of complex labels such as sentiment analysis, audio/video transcription and image translation It helps derive quality data at scale and improves quality result development. Customer service & marketing virtual digital assistants As the name suggests, virtual digital assistants can comprise anything from intelligent virtual agents to virtual customer representation and chatbot. As is with the chatbot, we already seem to have certain knowledge about this tool. It is programmed with AI to aid in customer service when humans are away so as to keep the services flowing and offer better customer experience when they visit your website. Well, customer service & marketing virtual digital assistants are a tool integrated with Artificial intelligence capabilities and pre-built human inputs to offer automated service and information to humans. When it comes to providing answers to regular customer queries, handling customer grievances, or fulfilling customer requests, this virtual digital assistant is used widely. From the customer perspective, a virtual digital assistant is important to contribute to the personalized services to customers. Since consumers are twice as less likely to contact customer service, they want self-service. And virtual digital assistants fulfill that demand. When you implement AI-driven virtual digital assistants, they give more control and convenience to customers to resolve their queries. Benefits It improves cost-reductions It encourages human-resource savings improves response time that offers scalable and consistent answers to customer inquiries or employee requests to fit their needs improves customer satisfaction by offering instant and immediate automated customer service offers personalized and varied customer service for customers across widespread channels like web, social media, and messaging bots Offers in-depth insights into customer behavior that helps improve product and service depending on the conversations taken place Helps enhance sales growth while decreasing shopping cart abandonment with constant personalized recommendations Better compliance with security standards as it is programmed to offer a set of service or actions Digital Experience Marketing Marketing professionals are aware of the AI capabilities that help in improved decision-making, better customer engagement, and growth of revenues. Despite these high-performance capabilities, only 18% of marketers implement this technology. McKinsey & Company reports a wide performance gap is likely to be visible between AI adopters and non-adopters in marketing activities. While AI adopters are projected to double cash flow, the non-adopters are twice as much likely to suffer financial debacle up to 20% by 2030. So, if you are not determined to implement AI into your marketing strategy, it is time to rethink based on its useful use cases we are highlighting here. Benefits AI improves better optimization of advertising resources by discovering if the advertising strategies are worthwhile. AI technology helps marketers use accurate attributes to specific advertising prospects and foster sales. It is not possible for every customer service team to devote an exact amount of attention to its customers. With AI-based solutions, marketers can use customer historical data to predict their preferences and get better insights into developing competitive services and products. The step towards mitigating customer churn as a means of customer retention works as you could identify risks ahead of time. AI looks into buying and browsing behaviors of customers and understands customers’ perception of a brand. Overall, this improves the customer experience while improving product recommendations to lead to increased sales. Brands can also leverage AI-enabled facial lenses and neat filters that enable image recognition. They can use this feature to connect with audiences on a personal level and improve brand exposure. It enables sentiment analysis to find what people are talking about your brand on various social media platforms. It is a useful way to enhance observation and find causes of customer dissatisfaction. The visual search tool is another phenomenon of AI that augments the trend of image-based search. It makes shopping convenient for users. eCommerce and Sales Virtue Digital Assistants Be it a chatbot, intelligent speakers, digital virtual assistants make it all for your eCommerce sales growth. We know that virtual digital assistants are an interactive or conversational tool programmed with machine learning of NLP features to establish communication with users and solve a specific query of customers. Voice commands are a new dimension to augment eCommerce search. As a result, we are seeing the growth of voice commerce. And the best thing, it drives sales for you. Benefits It provides recommendations to suit the current inventory and influence the most static customers with personalized recommendations and lead a purchase. Clothing brands are most likely to leverage the capability of eCommerce virtual digital assistant and reduce eCommerce fulfillment issues. Your eCommerce virtual assistant never sleeps. They are awake all-time through to guide your customers and solve questions at any point of the day. It entices online shoppers with an instant popup of deals and coupons to influence impulse buying and leads sales. Conclusion AI is multidimensional and every business service can benefit from its wide range of service offerings. From marketing applications to customer service, AI offers next-generation applications for businesses. We at SynergyLabs watch closely the unique demand of clients and offer scopes to lead. For AI-related assistance and service, you can get in touch with us.

Artificial Intelligence is adding value to the business for a long time now. AI applications such as automation, data analytics, and natural language processing have already brought a drastic overhaul to business by streamlining the work process and improving efficiency. It is a powerful force that drives businesses and brings data-driven results. However, to narrow your scope for the AI capabilities, you must have some AI strategies. It helps you free up resources as you get better insights into where in your business operations you need to employ this technology. Here we are presenting some of the most business-critical use cases of AI that are poised to enable work more accurately and efficiently. Facial Recognition Facial recognition could be overwhelming for businesses for its positive impacts it is creating every day. Cutting through the noise of the industry, facial recognition merges with computer vision and machine learning to help us predict norms so that we can solve a dozen of human problems. As facial recognition is geared up to be disruptive, it is the frontrunner among wide AI-based technologies; it offers you more options to leverage its benefits through different applications in the industry. =">" Surveillance:="Surveillance:" More="More" Than="Than" a="a" Physical="Physical" Security="Security" Component="Component" and="and" Its="Its" Smart="Smart" Use="Use" Cases="Cases" in="in" Public="Public" Sector="Sector"> Benefits Access control is the leading field to leverage facial recognition capability. Facial recognition ensures authorized access to personal devices, vehicles, residences, and offices. Having this in place boosts your security and prevents unwanted and unwarranted security breaches of your devices, cars and office premises. More interestingly, it can detect any unscrupulous behavior of a person who is intended to dupe you. It eases attendance tracking and gives you better control over your supervision. It offers a better means of curbing truancy by personnel devoted to a specific responsibility. From a marketing perspective, facial recognition technology mounted to the surveillance can offer better insights into customer behavior or brings forth user preferences of the target audiences. Using text mining, this technology gives you options to give more choices to the buyers Facial recognition bolsters security for the banking system by offering multi-factor authentication. This reduces the number of frauds. For public security like schools, this technology is important. Facial recognition can be used to alert the doubtful behavior of persons when something suspicious is detected. Facial recognition improves disaster response and recovery. It provides real-time and contextual alerts to notify the responders so that they can take appropriate measures to mitigate the risks for the specified person. Human Emotion Analysis Human emotional analysis with AI-based technologies is used as a medium to detect human emotions and feelings. Although technology is an age-old system, AI or machine learning is the new entrant to human psychology. And it is devised to bring them together for an improved and engaging experience for users as well as business. A better knowledge of emotion and sentiment analysis will enable us to create empathetic customer and healthcare experiences, transform teaching methods and find out better mediums to suit our needs. However, it is not easy to analyze emotions in the first phase. It is complex and deceptive since it is expressed in different ways. We express our emotion through speech intonation, facial expression, our body language, and text or words we write. All of these institutes are a platform for emotional analysis. And these varieties have opened the growth of different variables to be assigned to emotional patterns to better understand its variances. As we cited earlier, a dozen sources of emotional patterns, AI-based human emotion analysis tools derive into real contexts from these sources and suggest better predictions or metrics for us. For example, from a facial image, an emotional analysis assigns different scores on the expression including happy, sad, anger, disgusted and quiet. Let’s see how this helps your business. Benefits AI applications identify the consumer’s emotional condition and suggest appropriate responses. Imbued emotional qualities and empathy, when applied with AI, can boost patient care experience in certain cases. The application helps derive reactions from marketing strategies such as campaigns, products, and services. Emotional AI tracks conversation of callers, detects their reactions -angry or sad and streamlines appropriate workflows. In market research, the emotional analysis uses some advanced metrics to gauge the reactions of people towards new products. It helps improve in-store shopper experience with improved emotional analysis features for retail campaigns. Intelligent Customer Relationship Management systems No business process could be invented without the pre-built strategy for customer relationship management. If you fail to come to the expectations of your customers, it is more of a do-or-die situation for your business sustainability. We know an efficient and robust CRM tool lets every business streamline, organize and automate every aspect of customer conservations. If you have it in place, it can serve a dozen task accomplishments at one go. You can check with your marketing, sales, customer service while managing everything very efficiently. Research shows, CRM growth is likely to reach $394 billion in revenue by 2021 when combined with AI. AI-powered CRM solutions now feature face and voice recognition to access information. With AI-enabled CRM, you can foster a digital transformation by finding new customers and retaining older ones. Benefits The built-in virtual assistant and bots in CRM interact with your customers and accelerates the sales cycle. It helps you schedule meetings, automate report generation and capture data to build more accurate marketing campaigns. AI-based CRM studies historical data to improve its mistakes and take more insightful actions to make sales successful. Price optimization is one such trait of this system that assigns accurate prices on the discounted products to attract potential buyers. This saves you money on marketing campaigns as you use historical data to maximize prospective customers’ preferences. It enables emotional and sentimental analysis so that you can extract exact information from customers’ reactions and offer real-time customer satisfaction. AI-based CRM allows customer segmentation. It cuts manual jobs of data entry and delivers messages to a specific group of customers. Real-time notifications when sales possibilities are not generated at regular intervals. Intelligent Recruitment and Human Resources Systems Not only does it fit into autonomous cars and humanoid robots, but AI is also smartly integrated with HR systems. AI enables many of your human resource tasks and is reimagining the future of talent acquisition. Artificial Intelligence is an enabler of employee onboarding and administration for HR. According to reports from IBM, 66% of executives believe the cognitive intelligence of computing technology is likely to transform major areas of HR responsibilities and improve the employee experience. Even if it is in its infancy stage, and not perceived as an important parameter for business leaders, it offers some dramatic business outcomes. Benefits It allows easy and agile onboarding for new hires with personalized employee experience. As is with AI-powered HR, it is programmed to convey employee information on the mobile device and also new assignments. It helps make day-to-day decisions about work. For example, when it is regarding a vacation request, an AI-integrated system tells you that others have already taken vacation leaves in that particular time frame, hence leave is not granted. With employee monitoring AI software, it tracks employee activity, their browsing history and also analyses communication tone to extract meaningful data and make predictions about employees wanting to leave the job. AI in HR removes bias patterns from the workplace and makes it as diverse and inclusive for every employee. Interview scheduling is trouble-free with AI-powered HR tools. It uses different channels to connect with candidates, learns about their skills and knowledge. It then introduces the candidate to the company using ML. Conclusion AI is slowly becoming the voice of almost every industry. That’s because AI enables you to get better ideas and scale your business. SynergyLabs is an AI consultant that uses ML tools and algorithms to build AI-powered products and solutions for you. To design, integrate and deploy your AI products, do get in touch with us. We are more than happy to help you.

AI is no longer a secretive technology to garner exciting and amazing business benefits. It is ubiquitous even in the most neglected activity such as those mails that automatically make it to the spam folder. Also, let’s not forget those predefined suggestions for composing a new mail. It all lies in the cognitive intelligence of deep learning or machine learning that enables these predictive performances ahead of time. However, the scopes and capabilities of AI are beyond these mere accomplishments. Businesses can build up their cognitive capabilities to satisfy their business objectives. So, it is imperative for businesses to regard AI as business enhancement tools rather than a technology. Some interesting business use cases are there that help you unlock potential and seize the right opportunity ahead of time. The figure below shows varied degrees of AI benefits at business by industry leaders. Applications Of AI In Your Business We will discuss some of the AI-based components that empower and redefine your business. Let’s get started. Agent-based simulation In the age of rapid advancement of Artificial Intelligence technologies and machine learning that foster the growth of predictive models, agent-based simulation has become a reality. As we simplify the definition of Agent-based simulation, it refers to an Artificial-based computational simulation model of a complex system to simplify the understanding of a system behavior. It then imitates how the associated people interact with its surroundings and its institutions. Further, it also specifies how the interaction could precede some specific things to occur. The best possible application of ABM is to analyze complex and non-linear risks by improving decision-making faster and cost-effective manner. To aid financial services, this model is easy to scale while it is efficient in building more accurate and diverse computer simulation capabilities. ABM Benefits For financial sectors, ABM simulation fosters decision-making. However, different banks have different approaches to building models. This varies greatly impacting the development of better product and service and customer services. =">" The="The" Most="Most" Intrinsic="Intrinsic" AI="AI" Applications="Applications" in="in" the="the" Public="Public" Sector="Sector"> However, the core value of this data is to carry our sentiment analysis to understand customer behavior in different industries and find powerful and efficient ways to run all operations. Benefits Automated audio/video data mining is an extended part of image recognition and analysis. You can use this technique in different business applications. The key is identifying customer behavior. Cuts through the noise and derives essential information from organizations Distinguishes relevancy of data and finds ways to determine the right strategy Accelerates the decision making process It helps build engaging storytelling contents for business It improves brand awareness Accelerates business process Offers great customer support It can be leveraged for marketing purposes or analysis. Speech and voice recognition is used to know about a user perspective posting a specific product video on social media platform In a call center context, it can be used to transcribe audio/video data Using deep learning, text can be transcribe from video footage automatically Automated Report Generation Automated reporting provides you user-centric useful information in a timely manner. It does not need you looking for specific information; rather it generates reports on different variables such as various occurrences of your business and how different areas of your operations are functioning. At every fixed interval, automated reports are generated. For example, it could tell you about the weekly sales performance or shipping backlog may be triggered to remind you of immediate steps to resolve the issue. Benefits It helps you automate complete report generation for every aspect of your business As you reduce manual efforts in report generation, automated reporting generation uses AI to reduce the propensity of errors and provides you enough time to analyze reporting data It is either generated daily or weekly and dispatched to mail of you and your stakeholders to raise your awareness about the occurrences of your operations The automated report is also highly customized to fit the needs of the stakeholders It removes repetitive tasks and reduces human errors Faster and easier report generation that increases efficiency of the business Every business such as marketing, sales, IT, HR, and operations can benefit from automated report generation techniques Helps maximize ROI Business Application Virtual Digital Assistants Customer services have long been devised to offer seamless customer experience through automation with NLP and other forms of advanced artificial intelligence. Over time, the combination between ML, NLP and artificial intelligence have brought significant advances in digital virtual assistance which is now so ubiquitous in different enterprise levels. Today, the AI-enabled virtual digital assistants offer more beyond typical services such as customer service and marketing. From this perspective, it is quite useful and significant. There are three sectors that can generate more revenues and make proper use of virtual digital assistants, including e-commerce & sales, business applications, and healthcare. The foremost application of virtual digital assistants is to answer queries and perform actions via voice or text inputs. Benefits Virtual digital assistants can schedule meetings and reminders of upcoming events or meetings Reminds of upcoming tasks such as sending mails, photos, files, and docs and many more It implements automation to ease many of the actions such finding a location or translation of a foreign language It takes part in natural conversation with customers by explaining context and extending help via live chat when solving complex queries of customers to reduce frustrations. It offers industry-specific recommendations to improve marketing strategies. The Takeaway AI technologies offer a widespread scope for business use cases. If you are intended to simulate real-world insights into human language and behavior, virtual digital assistants are of great importance. For any kind of AI, ML and NLP solutions, get in touch with SynergyLabs. We are a true ambassador of AI services to transform your business and yield data-driven outcomes.

We have several emerging technologies such as blockchain, big data, cloud computing, and not to mention- Artificial Intelligence. Owing to AI, it seems to disrupt every business with its unprecedented capabilities and thus capturing a large chunk of the organization’s attention. Many companies are exploring various opportunities with AI to make them productive and efficient. The public sector is not too far from exploring its capabilities. As it brings forth an astounding potential, the government may look into this technology and harness its cognitive functions. With improved machine learning and AI capabilities, the world government appears more enthusiastic about AI research and development. As we bring you more applications for the public sector domain, the government can leverage AI technologies and bring operational efficiency for improved citizen engagement and experience. Let’s find some of the relevant areas to bring about improvement and put forth novel and innovative possibilities to harness more. Street Lighting Street lights are a major part of the government's smart city initiative. As opposed to traditional lights, low-powered LED lights have been in the operations to replace the burden of energy expenses of the public finances. It was devised to improve the energy efficiency demand for the environment and reduce carbon emission. But, do you think this lighting solution has rightly adapted to the growing needs of smart cities? Maybe not. Only the smart lighting solutions can complement the attributes of a smart city right after it dusks. Owing to the incapability of LED lights to be fit for automation, smart lighting can be automated to control its functions. This is necessary as lights in smart cities should always be in action with fewer changes in frequency. Smart Street lights integrated with IoT, smart sensors, intelligent management systems, and AI can do wonders for the smart cities. These technologies help us manage the intensity of public lights. Also, we can manage its shine specific to requirements. Thus, we can achieve real-time lighting resolutions with smart lighting systems that dim, turn on/off on different terms. The smart lighting solutions can also enable several intelligent applications, including robust parking management. Must Read: Case Study – AI In Rescue Of Car Parking Woes At The Busiest Shopping Center In Abu Dhabi Case Study: Warehouse Vehicle Parking Management With Number Plate Recognition Smart Lights And Parking Management – How It Works Together? Smart lighting solutions feature sensory nodes, which encompass powerful edge computing nodes. The system in use derives data streams from smart lighting, IoT sensors or video graphics and environmental monitoring. The data collected from the entire network can be utilized for citywide parking management. Cars can be parked anywhere on the city streets without many hassles. The cameras mounted on the street lights fetch data from license plates and analyze images with computer vision. The cloud-based management system connected with the motor vehicle database can provide accurate and real-time data about time incurred by the car, hence charging the exact amount for parking time during exit at the gateway. Intelligent street lights promotes improved public lighting management It reduces operational and maintenance costs It promotes energy saving initiative with advanced control over lights by replacing inefficient times and incorporating smart sensors It improves energy efficiency It reduces energy wastage by enabling controls over lighting intensity Faster resolution of maintenance work with real-time reporting and analytics With IoT platform, improved applications can be implemented such as smart waste Traffic Light Management The next big thing and application of AI is the traffic light management. It means when you implement AI to traffic light management, it provides dynamic traffic control possibilities. With better control over traffic lights previously executed by metronomic system, it guarantees improved and real-time traffic flow using cameras integrated with computer visions instead of timers. If it is in place, the government can strategize better methods to manage the traffic barrage of vehicles that creates unnecessary blocks on the highway or major streets during peak hours and normal days. How does it work? All it takes the AI-based smart traffic management system to adapt to the traffic signal timing. The computer derives video streams from one or more routes. It then analyzes traffic flow depending on the available video data. Later it decides how a change can impact the traffic flow against the predefined objectives. The computer vision calculates changes with respect of the traffic signal timing. As a result, it optimizes the activity of the traffic signal and determines better route to enable traffic flow. Benefits: · It enables real-time traffic flow using the dynamic traffic patterns that includes different modes of travel, vehicles, pedestrians, cyclists and many to keep transportation moving and every one safe. · Real-time traffic control to improve time-savings · Reduced carbon emission and improvement of air quality 3. Waste Sorting and Recycling We have tons of garbage generated every day. Currently we are dealing with 1.3 billion tons of municipal waste as per the World Bank. It is dreading as it is expected to grow to 2.2 billion tons by 2025. Isn’t a growing problem for waste management and recycling? Well, we can use AI for smart recycling and manage waste sustainably. With the advancement in Artificial Intelligence, to implement smart recycling for managing waste, robotic waste sorter can provide intelligence methods to get rid of the problem. · For Waste Sorting § Using RFID tags, it is possible to ease waste sorting. When tagged with the garbage buckets, the garbage disposal system reads these tags. By extracting data and parsing it, the system determines appropriate methods to dispose of the waste. § With smart trash cans that have inbuilt AI capabilities, you can speed the process of garbage sorting through a large pile. The system can identify and categorize type of waste and sort it inside the bin and dispose of waste with the help of machine learning. It also can refine its functions by analyzing historical data and improve its efficiency. · For Smart Recycling Recycling is important. AI-embedded trash can harness data with the power of sensors and machine learning to identify the garbage types. The interesting thing is, it can measure the weight of the trash in the bin, segregate liquid objects, and put the right garbage into the right can. It offers 90% of accuracy in recycling garbage and is perfect for high traffic locals such as shopping malls, and airports. Benefits The overall use case of this AI use case in the waste sorting and recycling is to foster efficiency in waste disposal and waste management. The use of advanced ML/DL tools can reduce human labor costs. It can easily augment the processes of the development of smart cities. 4. Weather Forecasting Weather forecasting is a challenging task. That’s because some technology such as Numerical Weather Prediction cannot offer actionable insights into weather behavior. NWP uses computational fluid dynamics and implements basic conversational laws and other external sources to determine weather patterns. It can offer weather insights on a large-scale, but some small scale matters such as precipitation do not receive accurate insights. Besides, the weather prediction reports of rainfall from storms and fierce winds are sometimes not accurate and reliable. AI-embedded weather forecast is way faster and better than traditional weather forecasting. By deriving abundance of weather information, Trained ML-based model can offer accuracy and efficiency about rare and extreme weather conditions easily. The US National Oceanic and Atmospheric Administration (NOAA) has been implementing AI to improve their understanding about weather forecasts. Benefits: · Quick and intelligent image and signal processing · Faster pattern recognition · Accurate prediction capabilities · Real-time weather data improves disaster preparedness response for high-impact critical events such as hurricanes, thunderstorms and tornadoes · Improves cost-savings The Takeaway It is definite that AI can offer us immense possibilities to enhance forward-thinking innovation at every scope of life. The public sector could be the next frontier that can implement AI to the largest potential and leverage its benefits. SynergyLabs inspired by thought leadership can offer better strategies for AI deployment in different areas of services. If you need any AI assistance, we can guide you on a successful journey. For more info about our products and services, contact us today.

When they are surveillances, we know how important these devices are that make lives and public places safer while securing the real-world assets. The trust for surveillance is so deep-rooted that we are more than eager to implement these technologies in the most critical places. Physical security devices such as surveillance are integrated with deep learning and artificial intelligence. So, how does it make a difference? This allows fast and effective data parsing and enables smart and data-driven decision making. This is enough to achieve your operational goals in security. Even though this is ascendant, the government seems to be not enthusiastic about this technology. But, in the context of its widespread use, the focus is now more than on its physical security capabilities. In this article, we will discuss some popular use cases of surveillance, which give you more reasons to maximize its potential and achieve amazing benefits for future operations. Surveillance: The Intelligent Side of AI Public safety is a key concern. Alongside, the security of property and facilities matters greatly. Many tools such as cameras, drones, and e-doors can keep criminals away, but video surveillance is of great importance. Over a few years, the use of surveillance has been increased in the places where goods are sold. AI prompts its growth and brings forward a dozen significant use cases. Must Read Case Study- How Synergylabs Helped A Renowned Shopping Center Improve Their Security With Facial Recognition Technology Crowd Controls And Monitoring In a large crowded area, AI-embedded surveillance can come handy. Areas such as public gathering in any sporting event, stadium, cinema hall or spaces such as airports where crowds must pass through a checkpoint can implement AI to further the detection process of the crowd by constantly monitoring their movement and anticipate future threats. As AI-integrated video technology such as surveillance can capture the movement and behavior of the crowd and keep a constant watch on them. Similarly, facial recognition-embedded surveillance can reduce bottlenecks at airports. This technology is useful in improving boarding processes and reduces manual labor. While this eases streamlining the passenger onboarding, it also intensifies security for people around as the system identifies criminals within the passengers. On the other hand, AI-surveillance video analysis helps identify individual criminals in the sea of the crowd in a crowded place like a stadium. So, AI is an added feature to security surveillance. Automation of Repetitive Tasks AI-based surveillance can easily automate repetitive tasks, which the traditional surveillance systems lack. The traditional surveillance tools require combing through lengthy video footage in order to harness the accurate information about suspicious activities. However, physical security tools with AI capabilities use different tags for images to facilitate fast information search, eliminating resourceful time being wasted after video footage search. As AI can distinguish every image and video, it can easily determine relevance. As a result, surveillance can accelerate the image search of concerned persons or objects. Detection of Left Object As part of smart cities, surveillance can better complement its objectives to make it a highly secured zone by deploying AI in its systems. As AI can classify between different objects and living organisms, it can detect anomalies easily. It can ascertain normal behavior or suspect something suspicious to ensure follow-up. For example, deep learning built-in surveillance can detect left objects like unattended bags or suspicious cars on streets or an airport. AI systems can keep track of every activity while security personnel or policies are not in action. This enhances the security of public property whilst prompting for quick action to mitigate any risks. Loitering Detection of Pedestrian Activity This is a phenomenal feature and application of surveillance to immediate action that stops suspicious activity if any. Using image analysis specification, surveillance can monitor the loitering of an unusual person for indoor/outdoor operation. It detects humans as they remain in the scene longer than expected. The surveillance is capable of working even when the person remains static. With the tool, it is easier to track the loitering of a person and avoid future risks immediately. Conclusion AI systems, especially surveillance are efficient in detecting potential suspicious behavior or identifying anomalies. But, it should sync with humans to enable faster and smarter accomplishment of jobs. AI has powerful capabilities and cognitive intelligence to reduce crime and ensure security for everyone. SynergyLabs offers comprehensive AI solutions for significant applications both in the public and private sectors. For any product related AI services, you can get in touch with us.