# A Review of In-Situ and Remote Sensing Technologies to Monitor Water and Sanitation Interventions
## 2 Sensing WASH
### Water Service Delivery and Use  
Water flowmeters are commonly used to measure service delivery and enable billing for the municipal water supply of many cities. These meters vary in functionality and form, from mechanical meters that are manually read to remotely reporting sensors. A challenge facing water service providers and customers is so-called non-revenue water (NRW)--that is, water supply lost in system leaks or used by people but not paid for. In developing countries, leaks alone have been estimated to cost more than $40 billion per year, with a loss of 45 billion liters of water--enough water to serve 200 million people. A further 30 billion liters is lost to poor metering or billing processes. This negative feedback loop diminishes the capacity of utilities to deliver reliable, safe water, and the willingness of customers to pay for this service. Improved water meters and processes can reduce this NRW gap, and improve the quality of water service delivery--and consumers' faith in it. In India, NextDrop [39] technologies have combined remotely reporting water meters with periodic water quality tests to reduce water consumption, leaks, and service outages. Also, in South Asia (India), the social enterprise Piramal Sarvajal [40] developed a reverse osmosis water treatment tool, \"ATM\", that continuously monitors and remotely reports on system functionality and water quality. Internet-connected sensors--including smart flow and pressure meters, water quality sensors, smart water consumption meters, and leakage-monitoring sensors--identify flaws and deficiencies in water distribution networks. In Sub-Saharan Africa, around 1 million hand pumps supply water to over 200 million rural water users across the continent, yet as many as one-third of all such pumps are not working at any given time, with 30%-70% broken within two years of installation. In 2013, Oxford University set up a trial of mobile-enabled technologies for 66 \"smart\" hand pumps. The study demonstrated that hand pumps with cellular-network-enabled sensors, and that received a repair during the trial, had far less downtime: 2.6 days versus an average of 27 days. Also, participating communities were three times more willing to pay for pump services than they had been before the installation of the sensors [41]. Building on this work, in 2014, Portland State University, Living Water International and SweetSense Inc. installed 181 cellular-enabled water pump use sensors in three provinces of Rwanda. The nominal maintenance model was compared against a \"best practice\" circuit rider model wherein dedicated staff and supplies were assigned to pump groups, and an \"ambulance\" service model wherein sensor data triggered a service dispatch. In only the ambulance model were the sensor data available to the implementer and used to dispatch technicians. This longitudinal study demonstrated that a sensor-based service model for hand pumps in rural Rwanda was associated with substantial reductions in the time interval between breakdown and repair when compared with both the nominal service model and a \"best-practice\" circuit rider approach. Similarly, there were significant, and parallel, differences in the amount of time that pumps in each service model were functional. At the baseline, 56% of the implementer's pumps were functional, with a mean reported nonfunctional period of approximately 214 days. In the study period, the nominal maintenance group's median time gap between breakdown and successful repair was approximately 152 days, with a mean per-pump functionality of about 68%. In the circuit rider group and the ambulance service group, this time gap was nearly 57 days and 21 days, with a per-pump functionality mean of nearly 73% and 91%, respectively. Smart metering, an approach first matured in the power industry, allows a water utility to obtain meter readings on demand without requiring manual meter readers. A recent IDB report summarized the opportunities and limitations of smart water meters [42].