Rahul Yadav, Chief Technical Officer, Milestone Systems examines how AI and edge analytics are transforming video surveillance.

Technological progress

The rapid advancement of AI and edge analytics is revolutionizing the video security landscape, enabling smart cities and law enforcement agencies to harness the power of data-driven video technology for the greater good.

By leveraging AI-powered video analytics, open platform video management software (VMS) and edge-computing technologies, cities and law enforcement agencies can proactively respond to incidents, save lives and create safer communities.

At its core, a smart city is an edge-compute-connected city.

It is a connected city that brings together disparate technologies and data streams to enhance city life.

With an integrated data infrastructure, cities can harness technology to create a safer, more efficient and more livable future.

The integration of AI with video analytics is transforming video monitoring from a passive tool to a proactive solution.

AI-powered applications can process vast amounts of video data, detect anomalies, recognize suspicious behaviors and alert authorities to potential threats in real time.

This enables law enforcement agencies and city officials to respond swiftly and effectively to incidents, minimizing the risk of harm to residents.

One of the key advantages of AI-driven video analytics is its ability to learn and adapt over time by being trained through a combination of real-world data as well as synthetic data.

The more data the system processes the smarter it becomes, continuously improving the way it accurately identifies patterns and distinguishes between normal and abnormal behaviors – to ultimately detect potential threats and mitigate false alarms.

Another example of how this technology can be used is in the case of a missing person.

AI-powered video analytics can quickly search through weeks of video data from multiple cameras across the city in mere minutes to identify the person based on their general appearance (hair length and color, general height and size), clothing or other distinguishing features like a backpack or hat.

This technology can significantly reduce the time taken to locate the missing person, therefore increasing the chances of a positive identification.

The power of edge analytics

Edge analytics are playing a crucial role in this transformation of video technology.

By processing data at the edge, within cameras, sensors and other internet of things (IoT) devices, cities can reduce latency and bandwidth constraints, enabling faster real-time decision-making and action.

Edge devices equipped with AI capabilities can perform tasks such as license plate recognition (LPR), gunshot detection, people counting, vehicle tracking and object locating – all providing valuable insights to law enforcement officers and city managers.

Edge analytics also enable cities to optimize their resources and infrastructure.

By analyzing traffic patterns, pedestrian flow and vehicle counts, cities can make data-driven decisions to improve traffic management, public transportation and urban planning.

This not only enhances public safety but also contributes to the overall quality of life for citizens.

Smart edge technology strategies in common use today include:

Smart cameras are a key component of video systems, offering embedded AI capabilities for real-time video analytics.

These advanced devices can perform tasks such as object detection, LPR and behavior analysis without relying on central server resources.

Gateways and edge servers play a crucial role in video systems by acting as intermediaries between cameras, sensors and the central VMS.

These devices aggregate and process data from multiple edge devices, providing local storage and processing capabilities.

By reducing latency and bandwidth usage, gateways and edge servers help optimize system performance and responsiveness.

IoT sensors and devices are essential for enhancing situational awareness and providing context to video analytics.

These devices include sensors for environmental monitoring, access control and asset tracking, among others.

By collecting additional data and integrating with other systems, such as building management and industrial control systems, IoT sensors and devices help create a more comprehensive awareness of the environment.

Mobile edge computing devices, such as drones and body-worn cameras, bring the power of real-time video analytics and data collection to the field.

These portable devices enable situational awareness, evidence gathering and remote monitoring in a variety of scenarios.

By processing data at the edge, mobile edge computing devices provide immediate insights and support swift decision-making.

Unifying data for informed decision-making

An open platform, data-driven VMS serves as the central hub for smart city operations, integrating data from various sources, including cameras, sensors and IoT devices.

By unifying this data into a single, user-friendly interface, a VMS provides law enforcement and city officials with a comprehensive view of the city’s operations, facilitating informed decision-making and faster response times.

The power of AI and edge analytics lies in their ability to correlate data from multiple sources, providing a more comprehensive understanding of situations.

For instance, by combining video data with access control systems, LPR technology and other sensors, cities can create a comprehensive security ecosystem that can detect and respond to threats in real-time.

Moreover, the integration of AI with an open platform VMS enables the development of custom analytics solutions tailored to the specific needs of a city.

This flexibility allows managers to address their unique challenges and requirements, ensuring that the technology deployed is effective and relevant to their context.

Responsible data collection and use

As cities increasingly rely on AI and edge analytics for public safety, it is crucial to ensure that these technologies are developed and deployed responsibly.

Balancing the benefits of these technologies with the need for privacy and data protection is essential to maintain public trust and support.

To address these concerns, cities and technology providers must adopt a “responsibility by design” approach, integrating ethical considerations into the development and deployment of AI and edge analytics solutions.

This includes implementing robust data security measures, ensuring transparency in data collection and use, and adhering to privacy regulations such as GDPR and emerging AI-specific legislation like the EU AI Act.

Furthermore, it is essential to engage with the community and maintain an open dialogue about the use of these technologies.

By educating citizens about the benefits and safeguards in place, cities can foster trust and support for the responsible use of AI and edge analytics to improve public safety.

AI for the greater good

As AI and edge analytics continue to advance, the potential for transforming public safety is immense. The integration of these technologies with 5G networks, for example, will enable even faster data transmission and real-time response capabilities.

Additionally, the development of multi-modal AI solutions, which combine data from various sources such as video, audio and IoT sensors, will provide even more comprehensive insights for law enforcement and city management.

Likewise, the increasing adoption of cloud computing and the IoT will further enhance the capabilities of AI and edge analytics in public safety.

Cloud computing enables the scalable storage and processing of vast amounts of data, while IoT devices expand the range and granularity of data collection.

The combination of these technologies will create a more connected, intelligent and responsive public safety ecosystem.

By leveraging these technologies, we can build a future where no child goes missing without a swift response, where accidents and natural disasters are met with rapid, well-informed assistance and where dangerous situations are mitigated before they escalate.

As we move forward, it is essential to balance the benefits of these technologies with responsible technology development and deployment, ensuring that the power of AI and edge analytics is harnessed for the greater good.

By doing so, we can create a future where technology and human expertise work hand in hand to build safe and resilient communities.

About the author

Rahul Yadav is the Chief Technology Officer at Milestone Systems, bringing extensive experience leading technology organizations in diverse industries including media, public IT, consumer electronics and telecommunications.

Prior to joining Milestone, Rahul held various leadership roles at Bang & Olufsen, KMD A/S, TV 2 Danmark, Texas Instruments and Samsung Electronics.

He holds a Global Executive MBA from INSEAD, Fontainebleau, France and a Master of Technology (M.Tech.) in Digital Communication from the National Institute of Technology, Bhopal, India.

This article was originally published in the July edition of Security Journal Americas. To read your FREE digital edition, click here.