Client is a popular company delivering a wide range of products to various locations. Client offers personalized services to various industry owners such as household appliances manufacturers, consumer electronic goods manufacturers and more. Client is providing their end users with the best services and helps them earn customers’ trust.
An unprecedented spur in the digital commerce with the growing diverse consumer demands, product deliveries become more frequent. It even involves delivery of smaller product size. Warehouse management finds it tough to adapt to the changing business demand since they are unable to utilize the workforce at the right time and at the proper location. This builds up pressure on the managers as products pile up in the warehouse. A highly competitive and first moving functional unit such as warehouse distribution must align with their workforce in a proper manner to accomplish their tasks. Failing to do so, it leads to loss of customer loyalty and cost them potential business loss.
Customer has a major problem to optimize their workforce better due to poor management of attendance. Their inability to implement a robust warehouse staffing optimization leads to confusions and departmental silo. It highly impacted their product operation and result in drops in their overall performance.
Over time, they noticed their biometric attendance system had some loopholes. Staff misused it and sneaked out of the site whenever they wanted. Moreover, they tricked the system to use proxy in their place in case they came late. It caused a major impact on the production and proper utilization of time. They also observed a substantial productivity loss due to missed work hours by the staff. On the other hand, due to poor handling of staff attendance data, it cost them a lot of money after keeping the staff.
Client wanted to follow a new workforce attendance management policy so as to maximize their investment after the staff and implement a proper utilization of work. However, their key objective was to identify the staff entering their work site as well mark persons leaving the site. The whole action is aimed at reducing staff time wastage and optimizing their time in the robust work management.
SynFaceRec – an automated attendance system with AI powered facial recognition capability was offered for deployment.
Technical features of SynFaceRec
High rate of accuracy in identifying persons with user login
High compatibility with different age groups
Identification enabled even with higher penetration of races
Image recognition shot from different directions
The whole process of image recognition in the automated face recognition technology is enabled using convolution neural network or CNN based AI technology.
How we worked on the program
We at SynergyLabs decided to divide the work process into three stages.
Face detection – aiming at detecting face from the captured images
Extraction of facial feature points – identifying different facial feature points
Face Matching – assessing the degree of face resemblances to recognize the registered person. When not gauging the resemblances, the face of person is adjudged different.
As we deployed our SynFaceRec an automated attendance system with facial recognition capability, it facilitated a number of resourceful work accomplishments at an accurate level.
First of all, it provided us with real-time data of the employee attendance as well as their time spent on the site. Orchestrated on their work system, it allows for full space visibility of the employee movement and their active engagement in the work.
Functionality of the system
It took into consideration different parameters such as processed input images to identify the logged in user.
It calculated environment around the locations while capturing images. Finally, it recognized faces using different inputs from locations and special criteria.
We also examined a set of new algorithms to ensure its precision in accomplishing the tasks and delivering the correct results.
It helped with building a comprehensive automated system with facial recognition features. As a result, client was able to track their employee activities with higher degree of accuracy. Client was satisfied with the result our product offered to them. With an innovative facial recognition solution, client achieved a higher rate of staff optimization while maintaining a better balance in work process in the warehouse distribution.