Year: 2024
Type: article
Abstract: The Water, Sanitation, and Hygiene (WASH) sector is crucial to public health and achieving sustainable development goals. To enhance the effectiveness of WASH initiatives, it is essential to gather data from various sources, including Flow Monitoring, Water Point Mapping (WPM), mWater, Leak Detection (FMLD), and mWash. By implementing big data analytical tools such as Apache Hadoop and Apache Spark, this sector can efficiently store, process, and analyze large volumes of unstructured data within a distributed, parallel computing environment. Leveraging big data analytics in the WASH sector enables improved monitoring, visualization, equitable data-driven decision-making, post-implementation tracking, open data practices, and strengthened social accountability, ultimately supporting the sector’s development and sustainability.
Source: Amrit Research Journal
Authors: Binod Kumar Adhikari, Ramesh Mahajan
Institution: Tribhuvan University
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4406180134