How AI, IoT and Big Data Will Affect the Security Industry

Stanley Security’s IoT expert Moiz Neemuchwala explains why Big Data and artificial intelligence are poised to have a major impact on the security industry.

How AI, IoT and Big Data Will Affect the Security Industry

According to James Barrat, author of “Our Final Invention” and expert on the subject, artificial intelligence (AI) is the last invention the human race would ever need to continue to develop and perform tasks usually requiring human intelligence.

In the future — and, to be superior to their ancestors — machines and computer systems will reinvent themselves on their own. It may sound a bit scary, but definitely fascinating too!

Engineers and data scientists are pushing this frontier to the next level and setting the stage for this future to be a reality. Artificial intelligence is powered by processing data; however, data needs to be generated first and the security industry is playing a big role.

Data is generated in a number of ways, with sensors being the most common form and what has allowed for the age of Internet of Things (IoT, or Industry 4.0). In other words, sensors communicate with each other while yielding various forms of data.

For example, a video camera collects/records video streams with each frame consisting of an immense amount of data. This information is collected in data lakes, which makes it accessible when needed.

Data Able to Dig Deeper, Predict Better

AI can now be enabled through deep learning — a new area of machine learning research, which, over the years, has evolved from pattern recognition, the simplest form of learning. Large swaths of data, commonly known as Big Data, can be brought together to provide insights that were difficult to comprehend.

This ability makes machines learn and capture decisions on their own, based on parameters which they continually absorb and update as they process more data.

For example, the camera that captured the video frames comprehends everything it sees and defines several more parameters based on the millions of frames collected over time.

One of the most commonly used algorithms for deep learning is neural networks, derived from how the brain operates using neurons, hence the name. Neural networks are used in multiple applications like pattern recognition, optimization, prediction of outcomes, etc. — the first AI-based, self-driving car used neural networks, for instance.

Advances in computational technology along with advanced statistical modeling have made deep learning an actuality. The ability to run complex neural networks in real-time on multicore processors (GPUs like those from Nvidia), as well as on Cloud servers like Amazon AWS and Microsoft Azure has enabled machines in various shapes and forms to learn and improvise themselves.

Most importantly, the cost of doing this work is significantly less compared to innovation in the past thanks to plummeting data storage costs. However, there is still a long road ahead to get to absolute artificial intelligence.

Technologies are evolving and the process of collecting good, effective data has only recently begun. The basis for AI has been set, but innovation in making all the pieces work together is still a few years away.

Physical Security’s Intersection With AI, IoT, VR/AR

The physical security industry is expected to grow to $113 billion by 2021 from $70 billion in 2016, according to research firm MarketsandMarkets.

Bundling physical security with other systems, like Internet service providers (ISPs) providing home security systems, makes it a highly adoptable product for every home and business; however, this is one industry that is easily disrupted.

Older technologies are commonplace and the rate of adoption of newer technologies is slower than many other verticals. At the same time, AI would result in increased competition across several markets.

Multiple industries are employing AI techniques to improve their product offerings, but at the same time, are converging and entering markets that are not their core competencies.

AI has also reduced barriers to entry to new markets and it’s not surprising that we see numerous startups employing AI to solve myriad issues, including security problems. The adoption of IoT capabilities is increasing slowly, which has given the market players the capability to develop connected devices.

This has led to IoT-enabled analytics and a larger implementation of machine learning techniques in new products. The physical security industry is picking up steam in accepting this usage of AI and IoT.

Recently, technologies like drones and robots equipped with onboard AI and access control systems equipped with super-human facial recognition capabilities have come to market. Meanwhile, virtual reality (VR) and augmented reality (AR) have also found their place in the physical security industry.

The central question is not when will this all come together, but how? The thought of converging and combining all these technologies and capabilities together — from reasoning, knowledge, planning, learning, natural language perception and the ability to move and manipulate objects — is not that far off into the future, which can get the brain racing.

AI is certainly the future and a major enabler of innovation and competition that will certainly affect security integrators and their end users. Where we go from here, well, the possibilities are truly endless.

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About the Author


Moiz Neemuchwala is Innovation Product Manager – IoT/Big Data, Stanley Security.

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