NEC blends biometric technologies with Azure IoT for new manufacturing, retail solutions

NEC Corporation of America (NEC) announced demonstration of new Internet of Things (IoT) solutions for the manufacturing and retail industries. Built with Microsoft Azure IoT technology, the manufacturing solution integrates face recognition technologies and Factory Energy Management System (FEMS) with Azure IoT technology to create an end-to-end solution for factory maintenance, repair, and operation. Analyzing energy consumption data to identify maintenance needs and automatically creating work orders enables a preventive maintenance culture within the plant.

By integrating factory operational data with employee identification and the case management system, NEC’s solution also improves operational efficiencies and provides the basis for process improvements. The use of biometrics for identification raises security controls to new levels and removes risks associated with entry passwords.

The retail solution gives a retail establishment to understand the age and gender of shoppers and gathers information about their interests and purchases. Store management can refine store layout, product placement, marketing and promotional offers, and digital signage to improve operational efficiencies and the bottom line.


Both manufacturing and retail solutions rely on the integration of NEC biometric technology and Azure IoT technology including Microsoft Azure IoT Hub, Microsoft Azure Stream Analytics, as well as the Cortana Intelligence Suite. NEC has also incorporated Microsoft Dynamics CRM, Office 365, and Microsoft Band. The use of Microsoft’s cloud services simplifies deployment across multiple geographies.

While the two companies continue to engage in engineering collaboration focused on server, storage, and networking solutions, as well as SQL Server, the relationship has expanded to solutions that include Azure, Office 365, and Dynamics CRM across a number of industries.

“NEC is excited to be working with Microsoft on innovation solutions available to global customers through the broad reach of Microsoft Azure IoT technology. Our strength in biometric solutions provides powerful endpoints for IoT solutions for manufacturing and retail industries,” said Hiroyumi Inoue, Vice President Global Platform Solution Center, NEC Corporation of America. “While we are focused on manufacturing and retail solutions today, our offerings are applicable across many industries including public safety, transportation, and hospitality.”

“Once again, NEC is delivering innovative business solutions built on Microsoft platforms. The intelligence revolution starts with business, and by utilizing our Intelligent Cloud, NEC is helping business customers empower their employees and optimize operations,” said Çağlayan Arkan, Microsoft’s general manager of worldwide manufacturing and resources. “We are happy that NEC is joining us at HMI for a second year as we continue to define the future of Manufacturing in a Digital World.”

Earlier this month, NEC aligned with Dr. Anil Jain, distinguished professor of computer science and engineering at Michigan State University (MSU), set out to solve using a database of unconstrained images – also known as “faces in the wild” because pictures are pulled from sources like social media – Dr. Jain and his team (Dr. Dayong Wang, a postdoctoral researcher, and Charles Otto, a doctoral student) created an algorithm that generated a list of candidate matches to help identify unknown faces from surveillance camera footage or crime-scene images.

NEC recently partnered with Dr. Jain and MSU to license this large-scale face-search system and will use it to enhance its current facial recognition solutions.

“NEC has a very powerful face recognition software called NeoFace that was primarily designed for mug shot to mug shot matching,” said Dr. Jain, “and it has performed extremely well compared to its peers in that kind of scenario. So, they were looking for a solution for the problem where query images have rather large variability in terms of pose, illumination, and expression, and still need to be searched against large face databases.”

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