Asquared IoT: A "Sound Approach" to Industrial IoT

CIO Vendor Industrial Internet of Things(IIoT)or Industry 4.0 has the ability to enable manufacturers and OEMs to transform their industry operations by bringing advanced capabilities for smart manufacturing. However, despite this immense potential for growth, the successful implementation of IIoT is marred by challenges concerning interoperability,security, visibility and data analysis, where the vast amounts of data generated today call for advanced machine learning techniques to generate insights from the data. Recognizing these challenges, Pune headquartered Asquared IoT endeavors to address them with its Advanced Analytics and Machine Learning Algorithms for Industrial Internet of Things (IIoT).

Founded in 2017, Asquared IoT is the brainchild of Anand Deshpande and Aniruddha Pant,two Mechanical Engineering PhD holders with over 15 years of expertise in the diverse areas of Artificial Intelligence, Machine Learning, Mathematical Modeling and Computational Sciences, and Kanchan Pant, who has 15years of experience running a large manufacturing company and understands the needs of manufacturing very well. Leveraging this expertise of its founders, Asquared IoT has been focused on applying state-of-the-art Machine Learning techniques to explore data from Industrial IoT, gain insights into the data, and identify anomalies and machine/process failures. To bring this about, the company follows its own innovative approach of ‘edge computing’, which refers to the ability to run analytics algorithms and perform real-time analytics at the edge of IoT, there by facilitating real- time decision making. “Asquared IoT has been developing ‘edge computing’ based products with embedded AI and innovative sensing technologies, which are non-touch, non-intrusive, easy to deploy in any manufacturing plant, and easy to retrofit to even older manufacturing machines,” affirms Anand Deshpande, Founder & CEO.
Asquared IoT is also unique in the type of data and sensors they use. They use industrial sounds as the inputs, and a microphone as the sensor. They are the only company in India (and one of the only few companies world- wide) that does AI-based Sound Analytics on Industrial Sound to deduce real-time information from manufacturing processes. There are several mathematical challenges in processing and analysing sound, especially in real-time. Asquared IoT has the mathematical skills and prowess to do this complex math for sound analytics in real-time.

Among Asquared IoT’s suite of edge computing based solutions, Equilips 4.0 stands as the company’s flagship product that has been designed for easy and quick deployment at manufacturing plants, and is based on the sound analytics theme. As a completely non-touch and non-intrusive device, Equilips has the capability to “listen” to industrial sounds, and use embedded real-time sound analytics to identify the sounds and calculate performance and productivity parameters. Furthermore, one of the unique features of Equilips 4.0 is its ability to provide real-time quality measurement as well as operational statistics for manufacturing processes. “The key merit of Equilips 4.0 is its potential to generate digital data from an old machine which otherwise has zero digital footprint, and in the process convert a legacy, non-smart machine into a smart machine,” explains Anand.

Despite a recent beginning, Asquared IoT has built an expansive portfolio in the IIoT space and gained a good deal of industry expertise through its various engagements. Asquared IoT was selected by Cisco as one of the top tech startups for the Cisco Launchpad program, in November 2018. Under this program, Asquared IoT is actively working with technology, UX, and business experts from Cisco, as well as experienced mentors from Cisco and Silicon Valley.

Leveraging this position, the company is enroute to developing innovative solutions for many manufacturing processes. “The common theme in all these solutions will be non-touch, non-intrusive, sound and video-based real-time analytics using edge computing,” signs off Anand.