A future of flying cars and Minority Report-styled predictive dashboards may still be some time away, but the possibilities of robotics and Artificial Intelligence (AI)-powered automation are a reality today.

From connected cars to smart homes and offices, we see daily how big data and the Internet of Things (IoT) are changing the way industries and societies work. As we collect big data from sensors and devices, analytics becomes increasingly important in making sense of today’s connected world.

Data not analysed is value not realized. And that is an opportunity cost to organizations. Examples at a recent event include brain wave detection and image recognition to enhance manufacturing operations. Keep reading to learn more about the event and these exciting innovations.

Making advanced analytics and IoT innovation accessible to all

Together with industry leaders, Cisco and Cloudera, SAS is collaborating with Nanyang Polytechnic (NYP) to launch its Digital Engineering Innovation Centre (DEIC) in Singapore. Analytics-driven innovation often requires costly and sophisticated machinery and tools. Our collaboration with NYP’s School of Engineering affirms the commitment of SAS and our partners to provide students advanced analytics solutions to innovate, and it offers an environment where relevant industry use cases to be developed.

NYP staff showcase real-time analytics in the new innovation centre

SAS Intern from NYP showcaes how image recognition can be used in precision engineering

The setting up of this innovation centre also represents the coming together of the industry ecosystem with SAS partners Cisco and Cloudera. Bringing to life edge-to-enterprise analytics architecture, this collaboration means that real-time streaming analytics can now be done at the sensor and device level, and provide valuable intelligence.

Critical components, cutting tools, machine controllers, and data acquisition devices are becoming smart machines with various sensors (like temperature, force and vibration sensors) embedded. With SAS Event Stream Processing technology, we can easily track and trace statuses, and create a smart view to enhance real-time production line monitoring. Working closely with NYP to bring this to life, we showcased the following two use cases at the Centre.

Brainwave detection to alert or prompt machine operators

Operating machinery or equipment can be repetitive and monotonous. Together with the help of NYP students and staff, we developed models and algorithms to detect brainwave patterns, to determine if a machine operator is focused or sleepy when operating the machine, and send appropriate alerts or prompters. These alerts not only improve efficiency but, more importantly, prevent workplace injuries or incidences.

Enhancing precision through Image recognition

In industrial or manufacturing industries, intricate and precision focused tools and machinery are commonplace. With millimeters of difference in thickness and size between parts, very often, it’s challenging to differentiate one part to another. And unfortunately, using the wrong type of tools or parts can damage the machines – which can be costly to replace.

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