Applying various important technologies like machine learning algorithms and artificial intelligence have augmented the demand for video analytics.
FREMONT, CA: The implementation of significant technologies such as edge analytics, machine learning algorithms, artificial intelligence, and predictive and reactive analytics has increased the demand for video analytics. The demand also augmented in various sectors such as city surveillance, fleet transportation, retail, and law enforcement due to wireless aspects such as RFID.
Nowadays, due to incoming technologies, a massive amount of video data gets generated. Using human resources makes it impossible to manage and process such a significant amount of data, mainly due to restrictions in human capacity. Therefore, video analytics can be a helpful asset that can make video data valuable. It is possible to do video analytics in their different situations such as on-board real-time analytics, offline VMS forensics, and a developing field is known on-demand analytics by using the cloud.[vendor_logo_first]
Artificial Intelligence for Video Analytics
The automated solutions offered by deep learning and artificial intelligence will effectively analyze the massive amount of data that are generated by the videos so that it can provide better results rapidly.
The intelligent video analytics even utilizes deep learning so that they can recognize the facial structure. If the deep learning solution is well trained, it will also permit video analytics to rapidly analyze facial data by offering precise face detection with the better response time.
Deep learning technologies help in analyzing and processing large streams of footage.
Utilizing AI in video analytics will make it possible for many systems to communicate with each other so that they can help while making decisions and promptly capture any suspicious activities or even forecast them in advance.
Merging Video Analytics with Location and Identity-based Systems
There can be few situations where the camera might not take action due to obvious obstacles that are not involved in the algorithms of camera tampering. It means that video analytics will not work in such cases.
However, the combination of video analytics and other developed technologies that consist of Radio-frequency identification Systems (RFID) or Radio-frequency identification Systems (RFID) can offer a precise date or location.
