Edge AI sensing service

Empower your sensing solutions with edge-cloud synergy

Solutions

The edge of innovation: how AI sensing is already revolutionizing industries

1. Inventory monitoring

Example scenario: Retail/logistics

Monitor the status of product inventory and other information while ensuring the privacy of customers.

2. Inventory retention

Example scenario: Retail

Detecting the number of people who stop in front of each shelf on the sales floor, the average amount of time they stay, and the attributes of those people helps improve product layouts and lineups. Combining this with point of sales data makes it possible to analyze the correlation between the number of people stopping, the average amount of time they stay, and sales, ensuring a deeper understanding of improvements to be made on the sales floor.

3. Attribute/people count

Example scenario: Retail

Detect the number and attributes of customers that visit the store. The data obtained on the number and attributes of customers can be used to verify measures for improving the content of flyers and campaigns or to optimize product lineups and store layouts.

4. License plate recognition

Example scenario: Parking lots/logistics hubs

Detect the license plate details of vehicles entering/leaving the parking lot in real-time. Performing recognition processing, uploading the inferred metadata to the cloud, and linking with the payment system enables a smooth parking experience without requiring cars to stop at the gate.

5. Smart buildings

Example scenario: Buildings

Detecting how buildings and offices are used while maintaining privacy and confidentiality enables efficient facility operations, while connecting that data to systems that manage air conditioning and other equipment contributes to reduced power consumption and CO2 emissions.

Moreover, automation of visual reading of analog meters within the building through image analysis leads to labor savings.

6. Detailed analysis of employees

Example scenario: Factories

Analyze the tasks within the process rather than having analysis staff check or perform measurements with a stopwatch. Edge AI analyzes videos for visualization of the time required to assemble individual parts, identification of the amount of time that workers stop working for some reason, and more.

This can be applied to such efforts as standardization of process working time and analysis of problems, thereby improving productivity and yield.

7. Measurement of overall equipment effectiveness

Example scenario: Factories

Measure the overall equipment effectiveness (OEE) without customizing existing equipment. Cameras are installed for production equipment input and output locations, and edge AI analyzes the operating rate and performance.

Visualizing the production efficiency of conventional equipment allows review of the production line and quantitative evaluation of the improvement effect to enhance productivity.

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