A case for Wireless Sensor Networks

Stories of flooding and destruction from Burundi and the UK, are reminders of the vulnerability of our environment, and the need for measures to monitor and respond in time to extreme weather effects; this is especially true for flooding in Rwanda, given that one-fifth of Rwandan homes are vulnerable to flooding (according to NISR).
Aline Akintore
Aline Akintore

Stories of flooding and destruction from Burundi and the UK, are reminders of the vulnerability of our environment, and the need for measures to monitor and respond in time to extreme weather effects; this is especially true for flooding in Rwanda, given that one-fifth of Rwandan homes are vulnerable to flooding (according to NISR).

Various technologies exist today to support environmental monitoring and disaster preparedness. The technology of utmost interest to me is Wireless Sensor Networks (WSN).

Given the direction of Information Technology into the realm of Mobile Networks, Big Data and Cloud Computing, we should pay more attention to WSN.

A WSN is a network of autonomous, self-configuring sensor nodes that communicate using radio signals (it can be uni or bi-directional communication) to a central location. Think of these nodes as small computers, in a network topology, placed in the physical world to collect and transmit data for various functions.

Because I cannot get too technical in this piece, let me attempt to draw a picture. Think of WSN as a network (connected) army of agents put out in the field to collect specific data, share it internally and/or radio this data to a central command office. In bi-directional communication, the agents would receive commands as well. I hope this makes sense…

WSN would facilitate flood detection because with sensors at river banks, water levels could be monitored and alerts/warnings issued in the event of unusual activity. By combining information from sensors on water levels, weather conditions and rainfall supply, authorities could make decisions that would shape disaster management.

Take for example, landslides which are tied to flooding and torrential rains: by measuring moisture levels in high-risk areas during the rainy season,landslides can be predicted by detecting soil coming loose from base rock.

Flood detection aside, WSN could be utilised for so much more in Rwanda. In agriculture, monitoring and managing farm conditions could result in increased yield; for example soil moisture levels can be measured over an expanse of farmland and the sensor data sent to a central site. After harvest, monitoring storage conditions would guarantee fresh produce. In Rwanda today, realistically speaking, this would fit best on large commercial farms.

Wireless sensors could be utilized in game reserves to study the behavior of animals:studying the effect of climate and human factors would draw a picture of movement patterns, selection of habitat, to mention a few (I recognize that human presence in these natural habitats could change the behavioral patterns of animals, therefore care has to be taken). WSN could also facilitate the monitoring of seismic activity in the North-Western region of Rwanda.

The list goes on: healthcare delivery through remote monitoring, water and energy conservation, managing industrial conditions, traffic monitoring, and so forth.

You ask: but why WSN? These networks can be designed to operate with minimal energy and even use renewable sources such as solar energy. Equally importantly, unlike most networks, WSN don’t require existing infrastructure, as they are independent networks.

There are some limitations to the deployment of such networks in Rwanda today (which I will not address here) but a first step on the learning curve would be to explore this technology through practical academic research projects.

It is imperative that we invest resources in this relatively low-cost (yet state-of-the-art) technology and collaborate with experts in the field given the benefits of ‘high-res’ data for various functions, including preparing for hazards such as floods.

Twitter: @rwandalavender

 

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