IOT api build with fastApi and Sqlalchemy.

High-performance PLC polling gateway (Modbus TCP) with clean architecture in C#/.NET.

Lightweight Modbus TCP PLC polling utility for industrial monitoring and telemetry (.NET)

HVAC Range Deviation Forecast - v2.0 (Hybrid Model) Granite TS Embeddings + Statistical Features による高精度異常予測システム

A modular gateway and simulator for semiconductor automation, providing seamless equipment integration, real-time telemetry ingestion, robust control APIs, secure authentication, and deep observability. It accelerates development by simulating both factory hosts and physical equipment in a secure, scalable environment.

Amazon Lookout for Equipment uses machine learning to analyze sensor data from your industrial equipment and detect abnormal patterns that signal potential failures. It helps you avoid unplanned equipment downtime by identifying potential equipment failures before they occur.

AWS IoT SiteWise is a managed service that makes it easy to collect, store, organize, and monitor data from industrial equipment at scale. It helps you make better data-driven decisions, quickly compute common industrial performance metrics, and create applications that analyze equipment data.

Amazon Monitron is an end-to-end system that uses machine learning to detect abnormal behavior in industrial machinery, enabling you to implement predictive maintenance and reduce unplanned downtime. It includes sensors, a gateway, and the Monitron mobile app.

Industrial LLM Engine is an innovative and scalable solution engineered to empower large language models to understand and analyze industrial telemetry data, transforming raw measurements into actionable insights.

A semiconductor factory production management system developed using Java Spring Boot, integrating Apache Kafka and MQTT for real-time order tracking and equipment data monitoring.

This n8n workflow automatically monitors equipment health by fetching real-time metrics like temperature, voltage and operational status. If any of these parameters cross critical thresholds, an alert is instantly sent to a Microsoft Teams channel and the event is logged in Google Sheets. The workflow runs every 15 minutes by default.