Development of a Low-Cost, LoRa Based River Water Level Data Acquisition System

Requirements for the Interactive Sessions

Please download these tools:

1. Download and Install The Arduino IDE. There are options for different operating systems
2. Download and Install Arduino hardware drivers and code

Welcome to this tutorial session, "How to Develop a Low Cost LoRa Based River Water Data Acquisition System". This course is part of a larger project being conducted at the Centre for Data Science and Artificial Intelligence (DSAIL) – Dedan Kimathi University of Technology. The project involves the leveraging of IoT and machine learning for improved monitoring of water resources.

This work gives a detailed explanation of how an IoT infrastructure was developed to monitor the water level (stage) at several gauging locations along River Muringato in Nyeri County, Kenya. The project was named "Project Muringato". The IoT architecture included the components listed below.

Project Muringato Architecture Components

1. Development, test and deployment of water level sensor nodes to collect the river water level data
2. Establishment and analysis of a wireless sensor network for data transmission
3. A network server to receive the data and for coordination
4. Cloud data storage services
5. Data preprocessing (Quality Control), Validation and Analysis

The tutorial focuses on some of the architecture development steps involved in the realization of Project Muringato and also some of the water level data processing and analysis steps. Below is a list of the said steps.

1. The interaction with replicas of the sensor nodes used in data collection
2. Inclusion of the wireless sensor network component and the network server component to enable data transmission
3. A highlight of how to store the collected data in a permanent time series database on the KENET servers
4. A highlight of how machine learning can be used in anomaly detection in time series data