A low-cost cloud-extended sensor network for supervisory control

The current automation supervisory control systems are situated in well-restricted areas and require investments in computing hardware and communication systems. In machine automation systems, any additional computing hardware can be cumbersome to install, making upgrades hard to apply. This paper presents a cloud-extended sensor network with supervisory control in a public cloud. The hardware and cloud resources used in the solution are low-cost, reducing the up-front costs compared to the use of high-end components. The system collects data from ST microprocessor (STM)-based sensor nodes that send inertial measurement data using user datagram protocol (UDP). The sensor itself is a Bosch BMI160, a cheap and small inertial measurement unit (IMU). The system is designed to be used in machine automation applications where the frequency of the sensory data produced is hundreds of hertz. The system is to provide low-latency data transfer to the cloud. In the cloud environment, data is collected by a computing service that can be programmed to perform algorithms on it. The system is tested in a setup consisting of five IMU sensors and an angle measurement unit attached to a hydraulically actuated flexible beam. The test setup aims to update a local control system's parameters based on a cloud algorithm and camera measurements of the beam tip position. The control results and communication latency are inspected. The main advantages of the proposed solution are the simple system architecture and cost savings with the use of low-cost sensors and cloud resources. The focus of this study is the functionality of such a system; intricate security issues are beyond the scope of this study.