The Internet of Things already promises to transform daily life in rich countries. And a new generation of farming and healthcare techniques is improving the quality of life of the world’s poorest populations. Our partner La Tribune reports.
From intelligent refrigerators to home thermostat systems and connected cars, the web of connected objects will enable the birth of “smart cities” and even “intelligent regions”.
Many business leaders and high tech specialists believe this revolution will improve services for citizens (for example in transport and health) while bringing great advances in sustainability and resource efficiency.
But what about developing countries? Will they also benefit from cutting edge technologies?
Most probably. At least that is the conclusion reached by the International Telecommunication Union (ITU) and the American networks specialist Cisco, which they published last week (19 January).
The authors of this report see the Internet of Things as the key to low-cost connectivity that will transform millions of lives in developing countries.
Concretely, they believe this technological revolution could help achieve “nearly all the existing Millennium Development Goals (MDGs) and post-2015 Sustainable Development Goals (SDGs)”.
This conclusion was based on three factors.
The first concerns access to technology: systems linked to the Internet of Things are already employed in developing countries, and are often cheap and easy to replace. The basic infrastructure (Wi-Fi, internet cafés, etc.) is already well established in many developing countries, and the ITU estimates that, “In 2015, over 95% of the world’s population resides within the coverage area of a 2G mobile-cellular network (and 69% under a 3G network.”
The second is the financial accessibility of the Internet of Things. According to the report, “the costs of research and development in the Internet of Things continue to be absorbed by strong demand in the markets of developed countries”. What is more, the slight adjustments needed to adapt systems using the Internet of Things for use in developing countries are relatively inexpensive.
Controlling water quality
The third and final factor that makes the Internet of Things vital to the success of the SDGs is its adaptability. Many connected devices have very simple “plug and play” functions and do not require expert installation or maintenance.
Another important point is that alternative and economical energy sources, like solar panels, can power sensors and networks in areas without reliable access to electricity.
Daniel Kofman, the founder of ICT4V (Information and Communication Technologies for Verticals) believes this adaptability is the key to the success of the Internet of Things. Based in Uruguay, he works with academics and industry professionals across Latin America, linking big data with sustainable development projects.
“Agricultural development often causes water pollution, with contamination from algae and bacteria. Thanks to sensors linked to data processing systems, we are able to prevent problems with water quality,” he told La Tribune.
Working case by case
The information gathered by these sensors can help farmers to irrigate their land in the most efficient way. But it can also be used by individuals to ensure that the water coming out of their taps is safe to drink.
For Daniel Kofman, it is important to “work on a case by case basis and always take local needs into account”. Solutions provided by connected objects depend heavily on the ways in which people live and work in the areas where they are deployed, as well as the data available, so they are often difficult to replicate from one country to another.
Examples of the successful use of the Internet of Things in development projects include a programme to place sensors into water pumps in Kenya. These sensors give advanced warning of when the pumps, crucial for life in rural areas, will need repairing or replacing.
In healthcare, the American development agency USAID last year launched a programme to fight the spread of Ebola. Using sensors to gather data on patients in high-risk areas (temperature, heart and breathing rate, etc.), data processors were able to predict when and where an outbreak might occur and alert the emergency services.