Engenuity eViewIoT: AI Energy & Fault Detection on /IOTCONNECT

Most of the 5.9 million commercial buildings in the U.S. are under 100,000 sq ft and run rooftop HVAC units on basic thermostats, with no diagnostics, connectivity or data. Owners find out about problems only when equipment fails. Where smart equipment does exist, the data usually sits in a proprietary gateway or an unmonitored dashboard, and the insight rarely reaches the technician who could act on it.

Engenuity eViewIoT fixes this. It replaces the basic thermostat with a communicating device, normalizes data at the edge, and applies AI diagnostics in plain language a technician can act on.

Key capabilities:

Remote control and management: centralized HVAC and lighting schedules and setpoints for every site, from one dashboard or an on-site tablet. HVAC fault detection: on-device ML watches temperature, airflow, pressure and runtime signatures on every rooftop unit. It catches drift days before a comfort complaint and identifies the likely root cause at the zone and RTU level. Refrigeration health: walk-in and reach-in temperature alerts, plus a compressor degradation classifier at the edge that uses current and vibration features. Health scores and multi-model fault classification help protect inventory and food safety. Portfolio energy management: fleet-wide health scoring, a prioritized service queue, AI site analysis, automated pre-cooling and site-level metering to verify savings. Ask eView GenAI assistant: ask questions like "Which RTU is closest to failure?" and get answers from live fleet data in seconds, with a one-click summary for the technician. AI insights and equipment health: a common AI engine scores every unit using fault rules, anomaly detection and baseline degradation, then ranks actions by energy waste and repair cost avoided. ESG-ready reporting: interactive energy and ESG dashboards in Amazon QuickSight.

Architecture: the Engenuity Edge Gateway runs on AWS IoT Greengrass v2. It maps BACnet, Modbus, Zigbee and 0-10V equipment to Haystack / ASHRAE 223P, runs ML inference on the device, and keeps local rules running through connectivity outages. Avnet /IOTCONNECT handles multi-tenant ingestion, device lifecycle and OTA updates. It runs on AWS IoT Core, AWS Lambda, Amazon EventBridge, Amazon Kinesis, Amazon S3, Amazon DynamoDB and AWS IoT SiteWise. Amazon SageMaker handles model training, MLOps and OTA model updates to the edge, and Amazon Bedrock AgentCore powers Ask eView. Classical ML at the edge provides speed and resilience, while agentic GenAI in the cloud handles reasoning, fleet learning and retraining. Axsys Automation provides hardware and firmware services for rollout.

Measured customer results (Engenuity Systems deployments; results vary by site, equipment and baseline):

12–30% lower energy consumption 25–40% fewer unplanned service events 50–70% faster problem identification 30–40% faster deployment 8–12 labor hours saved per week per portfolio manager 60% less time on ESG compliance reporting Full ROI in under 18 months