Receive alerts and notifications on all critical operations for your equipment. IoTFlows Stream Analytics Engines analyzes each sensor in the sensors networks and identifies
critical health issues in real-time. Allowing users to stay up-to-date with all their processes and equipment.
Reduce costs, time, and improve operations through secure remote connection, control and fleet deployment. IoTFlows Encrypted Device Management allows users to deploy code
to a fleet of devices instantly, its encrypted remote access allows users to access any device from anywhere in the world securely, and it's encrypted APIs allows for secure control to any process.
Aggregate data from sensors, devices, operational systems, and enterprise systems to generate predictions on asset failures. IoTFlows Predictive Maintenance
provides operators, engineers, and planners detailed insights into possible failures and how it affects overall operations, enabling them to optimize their assets
and reduce maintenance costs.
Increase production, revenue, and productivity of each machine. IoTFlows AI Machine Optimization applies learning engines that give insights into machine optimization based
demand, scheduling, quality issues, and machine utilization, in order for industries to maximize their machines potential.
Aggregate data from sensors equipped on machines into a single stream at the edge to more accurately map machine workloads, inputs, and outputs.
Monitor and react to changing conditions in real-time at the edge and pass data to the cloud for further analytics.
Track assets throughout the entire supply chain, and monitor in real-time product quality such as vibration, temperature, and container opening.
Perform improvements on route planning and supply chain data.
Supervise and control various field devices around the world.
Transmit data from industrial automated systems to ensure overall control of machinery amid the production process.
Create virtual replicas of physical entities such as devices, people, processes, or systems that help make model-driven decisions.
Gain a deeper understanding of the real-world conditions to make necessary adjustments to the product or service.
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