No abstract

Residential water meters accommodate various methods of power provisioning. Electromagnetic and ultrasonic meters, for example, often rely on a battery-like external power source, whereas mechanical meters harvest energy from water flow through an impeller. Although energy harvesting (EH) minimizes maintenance needs driven by battery depletion/replenishment, placing a physical element into the flow adversely affects water pressure. This intrusive EH/sensing technique is not user-friendly either since the meters with impellers need to be embedded into pipes by skilled personnel. Hence, this paper proposes a non-intrusive sensor system powered by thermoelectric generators (TEGs) for plug-and-play water flow rate measurement. This system, equipped with a custom-made energy management unit (EMU), adopts ultrasonic sensors, a task-based computing scheme, and a LoRa module for autonomous sensing and reporting of the flow rate. After summarizing thermoelectricity and delta time-of-flight (∆ToF)-based ultrasonic sensing theory, we provide the system model and design details with a particular focus on the EMU. Then, we experimentally evaluate the system under varying conditions, demonstrating their impact on average sensing and transmission periods. The results unveil that our proposal can achieve high measurement precision (±1.4%), comparable to its intrusive and battery-powered counterparts, and thus has the potential of replacing the residential water meters.

This paper proposes a thermoelectric generator (TEG)-powered ultrasonic sensing system for non-intrusive water flow rate measurement. The limited power provided by the TEGs is handled by a dedicated energy management unit (EMU), allowing reliable sensing, computation, and transmission tasks. First, we introduce the delta time-of-flight (∆ToF)-based ultrasonic sensing and thermoelectric energy generation theory. Then, the design is given, followed by the system evaluation under different harvesting conditions to show their impact on average sensing and transmission times. The results revealed that our method could achieve high measurement accuracy (±1.4%), comparable to intrusive and battery-powered counterparts, thereby offering a "plug&play+deploy&forget" hybrid solution.