Video Surveillance

Video analytics: The next wave of video surveillance

The days of relying exclusively on 24X7 vigilance of security guards have long since passed. There have been innumerable instances when an investigation was solved in minutes using video analytics. We are at the cusp of validating what these systems could achieve in terms of exploiting the unfathomable volume of video data captured daily by millions of security cameras around the world.

We live in an age where data is more valuable than oil. People have started realizing the importance of having an infrastructure that takes care of the massive volume of data generated without getting compromised. The technology shaping the next leap forward – and accelerating the pace of change – is one that will drive dramatic change in all areas of society: artificial intelligence.

Video content analytics is moving beyond the old-fashioned detective work. It is no longer restricted to monitor crime, but gather data, analyze them, and provide intelligence, all in one single device. That is the power of analytics! It gathers data through video cameras at a faster speed and with intelligent capabilities, many are finding new ways to use it.

There are several examples of video content analytics and where it can be applied. In smart city installations, the built-in analytics in video surveillance is the new star of all products as it goes beyond just traffic management. It provides the advanced intelligence to monitor historical monuments, crowd management during festivals, and detect the air pollution levels, amongst others. Retail businesses leverage it for proactive, strategic planning to enhance the shopping experience, yielding higher sales and greater customer loyalty. Healthcare organisations addressing operational challenges like finding unauthorised people in restricted facility areas.

New trends on the block
The traditional video surveillance companies look at Deep Learning and Artificial Intelligence as a feature to run off their existing products offering a way to both differentiate themselves and beef up their existing product portfolio.

Embedded video analytics include, object and face detection, analyze image data when captured to effectively eliminate the need to transmit data to a central server. This, in turn, enables the efficient use of both transmission and recording bandwidth. Using analytics, some cameras can also be set to record video at a lower resolution and/or frame rate, and then automatically increase resolution and frame rate to capture higher-quality video when triggered by an event.

Security technologies have grown to monitor safety, security, and terrorism, both within buildings and public places. With the integration of IoT, we have a powerful platform in hand to help enhance safety, improve traffic flow and understand environmental impact to improve security and quality of life. However, end customers have over this time taken much more interest in making video work with the business enterprise to increase productivity and add value to systems.

Next leap in video analytics
An IoT sensor can often detect even more than humans, such as levels of pollutants in the air, noise level, and vibrations. For this reason, they complement many camera-based surveillance solutions as they allow users to monitor threatened areas, as well as environmental factors.

IP audio is another emerging technology for the security industry. It is an all-in-one audio system that can help improve security with triggered alerts, create in-store ambiance with background music and broadcast live or scheduled announcements at the right time and place, irrespective of the industry.

With the advent of AI and ML, we see acoustic analytics learning over time about the environment in which they’re deployed so they’re better able to distinguish the difference between actual intrusions and false alarms for example; a window breaking and a drinking glass shattering.

A more recent trend in the surveillance industry is analytics. Feeding analytics information into AI engines, not only provides us with an intelligent body of actionable data but serves as a basis for predicting future trends, patterns, and behaviours, which helps us improve a surveillance system’s decision-making capabilities over time.

Technology will help people manage their daily lives, and forthcoming technologies such as Facebook M will only build on this. Significant adoption of virtual assistants like Amazon Alexa, Google Home, Apple Siri, and Microsoft’s Cortana have all gained momentum over the last two years.

Application of augmented reality (AR) in enterprise solution is relaying visual instructions to technicians which will aid them in the real world. In certain scenarios, with the growing popularity and use of non-visual sensors and analytics to add accuracy and authenticity, video surveillance users will be using AR to centralize data sources together in a single view, enabling a more appropriate and quicker response.

Integrating physical and cybersecurity
At the vortex of the digital transformation of industrial assets and processes, we see a gradual convergence of physical and cybersecurity measures. One of the key roles played by video surveillance systems in this convergence is that they represent IT infrastructures that can be used to monitor physical areas. Hence, they can be flexibly integrated with other cybersecurity systems towards a holistic and integrated approach to security and surveillance.

We expect an exciting and demanding time in the video surveillance ecosystem with AI video analytics and IoT gradually having a major impact on it. Cloud computing and edge processing will drive acceleration in adoption of advanced video content analytics. With videos gaining more popularity, there will be an increased need to conserve bandwidth which will drive a surge in cloud migration. This opens a plethora of opportunities for advanced video content analytics that process data collected from cameras and multiple devices.

In 2020, we anticipate a continued migration to cloud computing and edge processing where we’ll see AI-backed video content analytics become much more widely adopted in many industries such as transportation, higher education, healthcare, retail and more. The market is maturing, and video surveillance manufacturers understand the customer pulse and how to apply AI video analytics and work the supply chain.

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