Material aggregation and automatic design linked with AI and CAD

By combining the know-how of 35 years of CAD development with AI, it is possible to recognize components inside paper drawings and automatically aggregate them. In addition, automatic design technology automatically replaces recognized components with CAD components that have been trained in advance, and automatically traces the walls of architectural drawings with CAD, reducing the work burden on designers and contributing to improved work speed. To do.

Behavioral Sales Forecasts and Optimal Follow-Up Advice

Learn the daily business report and help you forecast sales and plan your next visit. By using the sales forecasting model, you can predict how sales changes, changes in the region in charge, and the number of activities for each purpose will affect sales. In addition, we will learn the contents of sales activities for orders received in the past, and provide planning support for the most suitable visit schedule and activity contents for receiving orders.

Prediction of time series data using RNN

Use RNN (Recurrent Neural Network) to build a prediction model for time series data. By using RNN for information that changes in time series such as solar radiation, temperature, and weather, future solar radiation can be predicted.

An object detection model that streamlines learning work by transfer learning

We provide a consistent service from "learning data collection", "learning annotation creation", and "system screen construction", which are necessary for building object detection models. By learning an object to be newly recognized from a trained model, it is possible to construct a model that identifies and recognizes an object with a small number of training data.

Identify file features and extract similar files

Identify files using AI. Features such as drawings and other files related to design and manufacturing can be extracted and managed as an index. Since the file itself can be used as a file search condition, it is possible to perform searches that were difficult with conventional file management, such as searching for similar drawings and drawings containing certain parts.

Security solutions for IoT devices

You can securely manage and operate IoT devices without requiring specialized security knowledge. It provides security functions at various layers such as OS, application, data level, etc. By setting security policies in advance, unauthorized communication such as DDoS can be automatically cut off. The logs related to the OS, applications, and communications on each device can be centrally managed in the cloud, and the status of remote devices can be easily grasped.

Centralize and visualize IoT device information with non-plumbing

A platform for quickly and easily setting up a mechanism to manage IoT device data, such as vibration meters and thermometers installed in factories and stores. Functions such as "simulation model", "predictive analysis", and "process automation" required for IoT device management are provided as standard. In addition, failure prediction can be performed using the machine learning function. In addition, with the "Flow Builder" function, sensor data can be handled just by connecting dedicated blocks by dragging and dropping without a program.

Development examples for Showa Corporation

By managing the products with different lengths one by one, we can improve accuracy by inspection at the time of shipment and provide optimal inventory management. Cloths have the same part number but have different lengths for each one, and there are also many products with very different colors and patterns. Cloths piled high in the warehouse were difficult to scan with barcode labels and inventory was very difficult to control. Therefore, we use RF tags to improve the operational efficiency of receiving, outgoing inspection and inventory, and have introduced an inventory management system.

Development examples for major construction manufacturers

Demonstration experiment in a severe environment such as a dam construction site. This is achieved using a metal-compatible RF tag and a durable buried antenna. This system automatically records the entry and exit times of the dump truck to the construction site using RFID. An RF tag is installed under the dumper bumper, and the antenna is buried at the entrance of the construction site to read the tag and record which vehicle entered and exited when. The accumulated entrance and exit information is sent to the core system as dump truck operation results data.

Okayama Digital Museum Development Case

We propose Systems Nakashima's RFID know-how, including how to show digital contents as exhibits. An unprecedented “exhibit” has been realized. You can search for information (treasure) while freely operating dedicated equipment in the hall where 1 / 5,000 aerial photographs of Okayama city area and its surroundings and 1 / 1,000 aerial photographs of central city area are stuck on the entire floor. Space.

Development example for a major shipyard

This is an entrance / exit management system using RF tags (wireless IC tags) for safety and health management at shipyards. When the worker carrying the RF tag passes through the entrance gate, the worker ID can be checked without contact by the RF reader installed at the gate. Since the entrance gate is compatible with outdoor environment, it can respond to rain and wind without any problem.