Integrating Management of Sensor Data for a Real Time Decision Making and Response System
Estimated Release: 2017
Type: Decision Making Tool
Funding Partner: Australian Water Recycling Centre of Excellence, Singapore Public Utilities Board
Total Investment: $903,380 (Cash: $350,000, In-Kind cash and service: $553,380)
Principal Investigator: Jeff Neeman, Black & Veatch
Modern computer systems are available that can integrate the signals from numerous sensors in a water system and interpret the signals as alerts/alarms in a way that plant and distribution system operators can understand to improve their response to sudden DPR treatment process anomalies. Real-time detection of quality and treatment process deviations coupled with timely decision is of critical importance for DPR treatment technologies because there will be limited time to respond with corrective actions to quality problems prior to consumption by the public. Decision-making may be difficult in the context of a multiplicity of sensors and sources of information. The implementation of an early detection system able to integrate all these sources of information, compare historical data, detect anomalies, and automatically generate a series of alerts/alarm will contribute to supporting the reliability of DPR treatment technology systems.
Goals and Objectives
The goal of this project is to integrate existing treatment system information with available sensors to support real time decision making to monitor and operate DPR treatment processes efficiently. The ultimate goal is to increase public, regulatory, and utility awareness and confidence in the reliability of DPR treatment technology systems.
A data set of relevant and commercially available sensors will be assembled covering a variety of water quality parameters. A feasibility study will then be completed to develop quality assurance and quality control practices to confirm that the continuously generated data from multiple sensors is accurate. This information will be integrated into user friendly tool that can be integrated into available software systems to allow DPR system operators to make informed decisions based on the available data.