Digital water developments and lessons learned from automation in the car and aircraft industries

Abstract

The provision of water and sanitation services is a key challenge worldwide. The size, complexity, and critical nature of the water and wastewater infrastructure providing such services make the planning and management of these systems extremely difficult. Following the digital revolution in many areas of our lives, the water sector has begun to benefit from digital transformation. Effective utilization of remotely sensed weather and soil moisture data for more efficient irrigation (i.e., for food production), better detection of anomalies and faults in pipe networks using artificial intelligence, the use of nature-inspired optimization to improve the management and planning of systems, and greater use of digital twins and robotics all exhibit great potential to change and improve the ways in which complex water systems are managed. However, there are additional risks associated with these developments, including—but not limited to—cybersecurity, incorrect use, and overconfidence in the capability and accuracy of digital solutions and automation. This paper identifies key advances in digital technology that have found application in the water sector, and applies forensic engineering principles to failures that have been experienced in industries further ahead with automation and digital transformation. By identifying what went wrong with new digital technologies that might have contributed to high-profile accidents in the car and aircraft industries (e.g., Tesla self-driving cars and the Boeing 737 Max), it is possible to identify similar risks in the water sector, learn from them, and prevent future failures. The key findings show that: ① Automation will require “humans in the loop”; ② human operators must be fully aware of the technology and trained to use it; ③ fallback manual intervention should be available in case of technology malfunctioning; ④ while redundant sensors may be costly, they reduce the risks due to erroneous sensor readings; ⑤ cybersecurity risks must be considered; and ⑥ ethics issues have to be considered, given the increasing automation and interconnectedness of water systems. These findings also point to major research areas related to digital transformation in the water sector.