Abstract:
This report outlines the development of an IoT sensor system (Project Ewaso), capable of
water-level monitoring in rivers channels, with an aim of ensuring equitable distribution of
water and sourcing of data to quantify unsustainable water usage and catchment area
destruction. The paper also defines an application scenario in a specific hydrological region of
the Ewaso Nyiro basin in Kenya, highlighting the characteristics of data collection and
processing used. Fixed position node systems are described along with web-based data
acquisition platform developments integrated with IoT techniques to retrieve data. The
developed architecture utilizes the LoRaWAN - LoRa protocol to send real-time data packets
from nodes deployed to a server that displays, decodes and stores the data. From the server,
data can be transferred to a time series database, where it can be accessed and displayed through
different customizable queries and graphical representation allowing future use in prediction
machine learning systems. All these characteristics are presented along with evidence of the
deployment of different devices and of the IoT network infrastructure.
