Due to the large number of players on the market, the video analytics market is expanding.
Deep Learning and AI
Deep learning and artificial intelligence combine to deliver automated solutions that can quickly analyze the vast amount of video data.
It uses Deep learning in intelligent video analytics for facial recognition. A deep learning solution with a high level of training allows to analyze facial data faster. This results in more accurate facial detection and quicker response times, making it a powerful tool for facial recognition.
Deep learning technologies are also used to analyze and process large amounts of video footage.
AI in Video Analytics
It allows for multiple systems to communicate, making it easier to make decisions and catch suspicious activity or predict them before they happen.
Video analytics’ future will include more than static algorithms. It will also include an event- and authorization-based alarm system. Only the authorized person and relevant departments will receive the alerts.
This technology is helps in various sectors to recognize the faces of employees. The pandemic has prevented finger punch from happening. Face masks have a common practice. Many applications cannot handle biometric entry from remote workers, however.
Video Analytics & Work Force Management
Facial Identification Framework is not available for video analytics. This makes it difficult to verify the process due to the use of face masks, which are used for drawing facial specifications (jaw line, nose, mouth, etc.). ACSG Corp has created a software framework that addresses the needs of critical infrastructure protection organizations.
The framework extracts video analytics when the mask is not worn. This is the only company that can verify facial specifications even with a mask on. Analytics are obtained by analysing the facial alignment, head position estimation, blink detection, and other facial attributes. This framework uses deep neural networks to detect facial landmarks in real-time.
This technology is crucial for resource management across critical infrastructure. Companies are increasingly focusing on technology-driven operations in the face of the pandemic. This technology addresses many post-pandemic video analytics challenges and is extremely futuristic.
Because attendance is an integral part of any business’ daily operations, this technology can help prevent the spread of contact-induced infection. Organizations can identify their employees using emerging technologies without any major obstacles. Remote work is becoming more popular.
Since the pandemic, there have been many fundamental changes in critical infrastructure delivery. The challenge of workforce management is just one. Notable is the fact that new-age critical sectors organizations can’t just rely on AI to meet their changing needs, but they also need to make better use of AI-based technologies to support national productivity after the pandemic. The company provides innovative solutions over the long-term, can certainly play a significant role in this area.
Video Analytics Market
Due to the large number of players on the market, the market is expanding. These are the main factors driving the adoption video analytics solutions by enterprises and SMEs in various verticals, including BFSI and city surveillance, critical infrastructure and education, as well as manufacturing, defense, border security and retail.
Importance of Video Analytics in 2021
Video surveillance system can only be as effective as the incidents it can capture and monitor. The software will help you locate them. Video analytics can make your surveillance system more efficient and reduce the workload of security staff. It also helps you to capture the full value security video by making your system’s work more intelligent. Having Artificial based Video Analytics software is now a need of the hour in 2021 and many businesses have started using it.
