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Case Study OfIoT

CASE 1

Image analysis AI to advance toward a society of greater safety and peace of mind

Image monitoring services represent an area in which deep learning technologies are expected to be applied to bring improved safety and peace of mind.
Developed jointly with Secure and Top Data Science, the "Morpho Crowd Counting™" system dramatically reduces the operating costs associated with monitoring by evaluating congestion at event venues and sending automated alert notifications to the security center if the number in attendance exceeds certain levels, thereby ensuring the safety of attendees.
This system can be used not just at event venues, but in stores and offices.

Partner voice

SECURE, INC.

Beyond technological capabilities, urgency and flexibility are essential

Today’s society requires the swift provision of solutions suited to new modes of life. This challenging project included various new initiatives. Morpho worked with us from the stages of initial planning and software development to propose solutions, including various specific innovations, resulting in a recognition engine that used images from security cameras. Once the project was underway, they were extremely flexible in rapidly developing test models, responding to requests for functional improvements, and in other ways. All this made it possible for us to deploy solutions for customers in just two months.

Ryuei Murata
Manager,
Business Development Dept.
Product Development Sec.
CASE 2

Taking on the challenge of real-world exterior inspections using AI

The rollout of this project that targeted the replacement of the eyes of seasoned inspectors with a combination of cameras and AI required rapid improvements in both recognition precision and speed. Exterior inspection devices need to identify all defects in production lots, without missing anything. A defect that passes the inspection process and is shipped into marketplace generates quality issues. In addition, in manufacturing workplaces where high productivity is essential, defects need to be identified by inspecting products at a pace of just a few milliseconds per unit. We expect Morpho’s SoftNeuro® deep learning inference engine to contribute to the real-world implementation of AI-driven exterior inspection through high-precision, high-speed inference in edge devices.