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Multisensory AI Revolutionizes Real-Time Analytics

multimodal AI real-time analytics

Humans use their eyes, ears, and nose to understand their environment. iOmniscient’s AI-based analytics emulates these capabilities with video, sound, and smell analytics, all working together.

iOmniscient CEO Rustom Kanga cofounded the company 23 years ago—long before AI became fashionable. “It was different then in the sense that you didn’t have the same power in computers, so we had to design our algorithms to be much more efficient, minimizing the amount of training required,” Kanga says. This experience has been very useful in that today the company’s AI algorithms require minimal training and can operate without a GPU, significantly reducing both operational costs and time required to implement systems.

And because GPUs are very power-hungry, iOmniscient systems make the entire system more sustainable with a significantly lower carbon footprint. The company leverages the Intel® OpenVINO toolkit to optimize models while minimizing resource requirements and enabling use of more cost-effective hardware.

The company’s #AI algorithms require minimal training and can operate without a #GPU, significantly reducing both operational costs and time required to implement systems. @iOmniscient1 via @insightdottech

Delivering Outcomes with Industry-Specific Packs

With more than 70 international patents, the company offers many unique capabilities—such as being able to understand behaviors in crowded and complex scenes—but iOmniscient’s focus is not on selling products. Rather, it understands its customers’ problems and ensures outcomes. It has developed algorithms to address more than 300 use cases, which can be used together in different permutations to solve many industry-specific needs. Based on these, it has put together comprehensive industry packs for industries as varied as retail, railways, and intelligent traffic management. Today the company’s products have been implemented in 70 countries across 30 different industries.

For many industries, iOmniscient’s comprehensive industry pack solves a variety of problems.

Consider the retail industry, where management is interested in understanding the demographics of their customers and how long they spend in different parts of the store. Retailers may offer loyalty programs to provide their customers with special offers specific to their known interests. When shoppers move through the store, digital advertising displays can reflect the interests of people approaching the display based on their demographics.

In buildings, the iOmniscient system can provide gateless access management without the need for a database. And in a manufacturing plant, it can help with quality control and predictive machine maintenance.

Autonomous Response

“We realized very early that the real challenge was not just to generate information about what was happening in an environment,” said Ivy Li, cofounder of iOmniscient. “Our customers require systems to act autonomously to solve their specific problem.”

Take, for example, a typical incident in a public place like an airport or railway station. The iOmniscient system can detect an abandoned parcel even in a crowded location. The person who left it can be tracked anonymously. When they are located, the system can find the nearest appropriate responder, provide them with a video of the incident on their phone and tell them where to go and what to do.

So rather than being focused on a single detection algorithm, the system dynamically combines multiple algorithms to achieve the action required, which in the above case was to guide a first responder to handle the incident.

This Autonomous Response, another internationally patented iOmniscient capability, can reduce the response time for an incident by around 80%. In a traffic accident situation, such a fast response can be life-saving.

Solving Complex Problems at Lower Cost with Multisensory AI

“Our customers tend to be price-sensitive,” Kanga explains. “We’ve designed our solution such that it requires 90% less storage, 90% less network bandwidth, and less computing than today’s GPU-based AI systems, and it can work with existing low-resolution cameras.”

So while the company continues to build “best in class” solutions for its customers, it is also focused on doing it at minimal cost, which is achieved by designing the system to minimize its infrastructure requirements. The result is an intelligent multisensory analytics solution that can usually be installed for less than the cost of a video recording system.

This article was edited by Teresa Meek, Contributor for

About the Author

Brandon is a long-time contributor to going back to its days as Embedded Innovator, with more than a decade of high-tech journalism and media experience in previous roles as Editor-in-Chief of electronics engineering publication Embedded Computing Design, co-host of the Embedded Insiders podcast, and co-chair of live and virtual events such as Industrial IoT University at Sensors Expo and the IoT Device Security Conference. Brandon currently serves as marketing officer for electronic hardware standards organization, PICMG, where he helps evangelize the use of open standards-based technology. Brandon’s coverage focuses on artificial intelligence and machine learning, the Internet of Things, cybersecurity, embedded processors, edge computing, prototyping kits, and safety-critical systems, but extends to any topic of interest to the electronic design community. Drop him a line at, DM him on Twitter @techielew, or connect with him on LinkedIn.

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