The amount of video data generated today is exponential, with more and more created every minute of every day. The vast amounts of data available offers tremendous potential for analysis and integration with other systems to offer valuable insight into both security and non-security practices.
Artificial intelligence (AI) has emerged as a technology that can streamline this process by constantly learning and adapting to real-world scenarios. As a result, AI enables better decision-making.
For instance, AI can learn what a normal environment should look like based on continuous video monitoring of a designated area. In the case of anomalies to the “normal environment,” AI technology would classify those anomalies or irregularities as outside of that “norm.”
An office building might employ AI for human detection during off-hours to determine if someone is on the premises. In addition to being present during office off-hours, if a person is exhibiting potentially suspicious behavior — such as moving quickly or not moving in a single, decisive direction — AI can be used to alert a guard to investigate the video and take action if necessary. And by integrating with other sensors, such as access control, AI technology could proactively lock doors if and when suspicious behavior is detected.
This is just one example of the many benefits of combining video data and AI, which are by no means limited to security applications.
Additionally, shifting data storage and analysis to the Cloud brings even more functionality to an organization and improves its ability to make these critical decisions. By allowing end users to manage alerts and incoming issues from a Cloud-based platform accessible from anywhere at any time, situational awareness can be improved, and the safety and security of an organization is prioritized.
Expanding Security Into the Cloud
While AI certainly brings added value to video from a security perspective, it also expands video data application to aspects outside of security, most notably business optimization.
In the age of the Internet of Things (IoT), businesses have access to data generated by an unprecedented number of sensors, such as point-of-sale (POS), mobile devices, access control, HVAC and much more. There is tremendous potential for organizations to mine this data.
By applying predictive analysis to generate actionable intelligence, businesses can extract valuable insights from big data for making decisions that streamline operations.
But while AI and machine learning open new doors for leveraging video in ways that may have been unimaginable just a few years ago, the reality is that the majority of video data today is still not being used for applications outside of security. A frequent roadblock for expanding an application is the challenges associated with aggregating and correlating data from multiple IoT devices and sensors.
This is where AI excels, particularly in a Cloud-based environment. On-premises surveillance systems are traditionally deployed in one-off instances and are not part of an integrated network that includes multiple locations, making it difficult to easily accumulate data.
Cloud-based AI systems, on the other hand, bring together data across multiple sites for analysis on a larger scale to identify trends while also making proactive recommendations to users. In a retail or hotel application, for example, the data can identify parts of the day when queue times tend to be the longest and recommend adjusting staffing at those times to improve customer experiences.
Opportunities Abound for Cloud-based Video and AI
Despite the fact that most end users today rely on video for security alone, there is still tremendous opportunities for integrators. Cloud-based AI systems offer the potential to not only allow data to be mined in ways that simply haven’t been available with previous solutions, but they also empower users to access insights for a globally dispersed business from anywhere and from any device. This is done through a streamlined, centralized platform that can easily scale as needed without additional maintenance or hardware.
Integrators can deliver greater value by educating their customers about the benefits of applying video data beyond physical security applications. From the integrator side, recurring monthly revenue (RMR) is the lifeblood of security companies.
However, RMR can be difficult to generate from one-time equipment sales and installation, which requires constantly selling to new customers. Cloud-based AI systems, on the other hand, offer the potential for generating additional revenue from existing customers by offering value-added services using their existing hardware and systems.
For customers, the potential financial benefits are twofold. First, with no new hardware required on-site, they can derive greater value from their capital expenditures. Second, by aggregating data from a multitude of sensors across multiple business locations, end users can glean valuable intelligence from their video services, which can streamline operations, identify opportunities for improvements, and more — all of which can directly impact their bottom line for the better.
Once the benefits of the Cloud are realized by integrators, customers will also be privy to the value that it brings to their business and continue to adopt Cloud-based services and products into the future.
Integrators should be prepared with the necessary knowledge about AI, IoT and how both can work together with Cloud-based video services to form a powerful, integrated system for improving security and overall operations.
The time is now for video data usage as a whole, coupled with AI-assisted decision-making, and forward-thinking integrators and end users are already reaping the benefits of these predictive technologies.
Andreas Pettersson is CEO of Irvine, Calif.-based Arcules, a Canon group company.
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