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Diycam: Offering High-Performance Video Analysis Toolkit Powered by AI

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Gagandeeip Singh Randhawa,Founder & CEO

The growing demand for IPbased CCTV cameras is expected to drive market growth. These cameras are used for remote monitoring of indoor and outdoor spaces. New technologies such as AI, deep learning, and machine learning are being integrated into these cameras to enhance their video surveillance features. According to the latest market research report by Technavio, the global closed-circuit television (CCTV) camera market is expected to post a CAGR of over 12 percent. Integrating new technologies in CCTV cameras market, Diycam (Do It Yourself Camera), headquartered in Mumbai, offers simple to use IP cameras that don't require DVR or any cabling, just a power supply and WIFI internet connectivity to provide video surveillance.

“We are a team of young engineers who come from technical and marketing background. We extract value from visual data to provide edge & cloud-based video analytics using Artificial Intelligence (AI). Diycam provides various prototyping and custom solutions and services which include face recognition, weapon detection, car ANPR, ATM & bank security and safety & hygiene”, said Gagandeeip Singh Randhawa, Co-Founder and CEO, Diycam.

Customized Solutions and Services for Surveillance
When it comes to physical security, for instance, video surveillance is a standard solution. Yet, by introducing AI-driven video analytics software, video data can be
leveraged as intelligence in previously inaccessible ways. Diycam offers services and solutions which include designing, planning and development of custom hardware and software for the specialized project. These projects help clients to take computing to the edge instead of cloud in scenarios where project has specific requirements and doesn't want to have dependency on cloud computing. More so, being one of the very first companies to develop these solutions in India, Diycam offers high-performance video analysis toolkit to take edge & IoT data and business intelligence into the age of machine learning. The company uses a combination of machine learning, deep learning, and hardware acceleration through customizing MobileNet SSD, ResNet and more to provide various highly accurate analytics. These solutions help many industries like healthcare, retail, security, public services and many more to become more efficient and safer by improving accuracy and reducing human error through automation.

Diycam’s Face Recognition system makes it easy to add image and video analysis to its customer’s applications using Diycam API services


Furthermore, Diycam is transforming startups and enterprises with computer vision AI and custom made services. Diycam’s Face Recognition system makes it easy to add image and video analysis to its customer’s applications using Diycam API services Also, the company offers a weapon detection system that uses object classification AI technology which can detect guns including 3D printed guns. As soon as the weapon is detected, security staff will be notified in no time through SMS, email and app. Not only this, Diycam also offers Vehicle Classifier and License Plate Recognition system which is a Deep Learning-based powerful license plate detection, recognition, and search solution for Vehicle type detection and ANPR/ALPR. Taking ATM Security a notch higher, Diycam has developed a proprietary algorithm which is capable of recognizing the suspicious activities inside the ATM vestibule such as a person entering the ATM wearing a mask or helmet, an armed individual (carrying guns, knives etc.), a person spraying black spray on the camera or tampering the camera, and multiple customers inside an ATM for long time. As part of its AI services, Diycam can significantly reduce ATM frauds and robberies.

The company’s topmost priority is to provide secure and safe environment to customers and Diycam’s AIbased services can benefit various industries like banks, ATMs, hospitals, schools, airports, railways & metro stations and smart city project.