AI-powered Visitor and Security Management
When the COVID pandemic struck and a nationwide lockdown was announced in India, the Shree Siddhivinayak Ganapati Temple was shut down for the first time in over 100 years. The Temple which used to receive tens of thousands of visitors per day before COVID, was no longer open to devotees. In order to reopen the Temple to their devotees, the trustees of the Temple started looking at options on reopening the Temple, while ensuring the safety and security of their devotees, as well as their employees.
The temple authorities realized that the only way they could protect the safety of their devotees and employees was by implementing a number of newer technologies, including automated Covid-19 checks, online booking, virtual darshans. This was designed with the devotees’ health and experience at the forefront of its development. They also recognized that this wasn’t just a temporary solution, but rather one that could be used to increase the security and operational efficiency of the Temple for years to come.
Cynapto delivered an integrated system that incorporated these newer technologies, thus enabling the Temple to open its doors safely and securely to all its devotees. The integrated system consisted of a proprietary AI system, Native Mobile Apps, Desktop App, Web Apps, Cloud systems and several microservices. In addition, the solution integrates with the hardware devices such as thermal cameras, access barriers etc. with low-level SDKs.
In order to monitor the outbreak of COVID-19, Cynapto provides a consumer surveillance solution that is designed for enterprises. The system quickly identifies and notifies anomalies in real-time for actionable prevention and containment. Devotees visiting the Temple now have a more enhanced experience with Cynapto’s AI-powered Covid-19 monitoring system and contactless Visitor Management Systems. Cynapto’s solution is a highly scalable platform, handling up to 20,000+ visitors per day. The solution is integrated with other security tools such as metal detectors and thermal scanners, to provide real-time visibility into who is inside the premises at all times.
The system provides actionable data and intelligent alerts on abnormal events and crowd behavior from their CCTV cameras, allowing them to respond quickly and prevent loss of life or property. Cynapto’s sophisticated AI algorithms also provide analytics and actionable insights for enhancing devotee experience in various situations.
- Contactless visitor experience handling 20,000+ visitors per day
- Enhanced compliance with MoHFW guidelines
- Fully integrated and real-time visibility into visitor movements and security across the Temple.
- Cost reduction by 50-60% on the hardware used.
Intel’s powerful hardware and Cynapto’s latest AI-driven innovation has delivered a robust solution for Shree Siddhivinayak Ganapati Temple Trust. Our deep expertise in deep-learning systems enabled us to distribute and optimize the processing pipelines for higher overall throughput. The Intel servers are powered by Intel Scalable 2nd Gen processors and Intel Xeon Silver processors providing powerful performance and reliable computing. Additionally, The Intel OpenVino toolkit enabled us to optimize our deep learning models and deployment using an inference engine onto Intel hardware. The systems together are processing more than 2 Million frames every day.
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Our ultimate goal is to create a more secure world for all of us. Our deep expertise in computing, memory, storage and network architectures allow us to specialize in high-performance computing using CPU and GPU accelerators. Cynapto delivers a revolutionary platform to diversify use cases and enables AI-infused security infrastructure by converging compute power, memory, storage, and network in a single appliance. By deeply embedding our AI engine into your security infrastructure, you are able to intelligently act upon data as it flows through the system in real-time. This allows you to do more with your security investments by consolidating data and spreading workloads across areas of interest.