How IoT and Big Data are tackling Africa's problems

IoT projects in Africa are generating data that could help Africa deal with its biggest difficulties

Globally, machine-to-machine technology is producing more data than human intervention. In Africa such data is sometimes hard to come by since most companies haven’t fully automated their processes. Even those companies that are producing machine-readable data are not using the data effectively.

However, a couple of startups in Africa are looking to take advantage of the vacuum in this space to produce applications that could solve problems plaguing the continent. Startups are taking advantage of Big Data and open data available on the continent and are changing lives as a result.

Here are some companies and sectors that are implementing IoT and Big Data to solve Africa’s intricate problems.


From expensive fossil fuel to clean solar energy

M-kopa is probably one of the biggest success stories in terms of provision of solar energy instruments to rural East Africa. The company helps paraffin users, mainly in rural areas in East Africa, to abandon fossil fuel and turn to solar energy which is clean and cheaper.

The company has now spread its wings to over 500,000 homes in the region. This does not only mean revenue for the company but also investments in monitoring tools that churn out millions of bytes of information on a daily basis.

Andreas Fruhen the Director of Technical Operations revealed how the company is using IoT and cloud technology to generate data and manage its solar panel devices. Customers use mobile money to pay for their daily fees to use the devices. MKopa Solar also uses text messaging to turn off devices not paid for.

“All solar systems are monitored in real time through the cloud,” Fruhen announced at a recent tech event in Nairobi. “Five years [ago] when we were founded nobody was thinking about IoT or Big Data but now we collect over 30 million payment notifications every year.”

He added that they have more than one million device readings every day. This is from the batteries to temperature of the devices and sensors. Additionally, they have geographical data on where the devices are located. They also have 450,000 rooftop sunshine readings every day.

They have calculated that they have saved their users US$338 million since they started, five years ago.

“Cloud is the enabler for all these,” he reiterated. “We have 680 terabits of data on our platform.” The company has used its data to provide upgrade devices to users who have finished their solar loan. These include buying television sets and water tanks.


Boosting food production in Africa

Africa is a sleeping giant when it comes to food production, but lack of management is seeing a lot of price surges for produce, making the market largely unstable. Africa heavily depends on rain fed agriculture, but some entrepreneurs want it to be data fed.

Listed in the World Banks’ Open Data Impact Map, over 38 organisations and startups are using Big Data to provide information on how farmers can either grow or sell their produce.

“The organisations use open data to provide solutions that better inform farmers’ decisions on managing their farms and increasing their crop yields. They primarily use agriculture, environment, and geospatial data,” the report said.

Farmerline, based in Ghana, gives farmers best practice information through text messages. According to the report, “Farmerline addresses both these issues, providing local farmers access to accurate, up-to-date weather forecasts and market prices. In turn, the farmers gain immediate knowledge of competitive pricing and if not larger, steadier yields due to the agronomic tips and support.”

Kenyan-based M-Farm also used big data to provide information on weather and crop prices. M-Farm uses data from Famine Early Warning System dataset on agroclimatology provided by National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), US Department of Agriculture (USDA), and US Geological Survey (USGS).


Educating the masses

Recently, Safaricom, Kenya’s biggest telecom company invested in Eneza Education, a startup that aims to help learners in schools brush up on their education using the mobile phone. The company says it has captured 1.8 million users in Africa and aims to spread their services to capture 50 million people.

Students can subscribe to daily questions either through USSD or the Android app and they send answers. They are then graded.

Such innovation enables tutors and teachers to easily track the progress of each child or a group of children through data analysis - all of this by using relevant and ready technology, the mobile phone. The company has completed 14 million questions since its inception, and they have seen general improvement of students using the service.

Eduweb, a Kenyan online directory for learning institutions has also been mentioned by the World Bank’s Open Data Map project. The site, which started in 2012, takes data on learning institutions and makes it available on the web for free.

Interested users can search for primary, secondary and post secondary schools and have their locations mapped out.

“The portal, which is also available on mobile phones, aims to help parents looking for schools for their children, graduates looking for post-secondary opportunities, or others generally seeking to further their education. While making use of open education data, such as the names, locations, contacts of schools in Kenya,” the World Bank said.

The application enables potential students and their parents to make the right decision in terms of searching for the right institutions to go to and which courses to undertake.


The need for machine readable data in Africa

Most of the data generated on the continent is still manual. The introduction of IoT tools and mechanism can automate the generation of data, making it less prone to mistakes and can be easily analysed.

In a blog post on the World Bank’s Open Data Impact Map Project, Audrey Ariss, a Researcher and Designer at Centre for Open Data Enterprise, says that most data generated are still not machine-readable.

“While all the organisations in our study used machine-readable data in their work, half of them told us that the majority of the data they need is still only available in PDFs, images, paper reports, or as website text,” she said.

She added that, “Over three quarters of the organisations stated formats were a barrier to data use. This is especially the case when working with large, historic and geospatial datasets. For example, organisations most benefit from geospatial data when it is highly detailed and available in shapefiles, GeoJSON, or CSV - formats that can be utilised by a computer - rather than in image form as it is too often provided. Similarly, census data is especially valuable when it can be accessed in bulk and is available in CSV or other machine-readable formats.”

All the same, as companies and government institutions digitise their processes, computer generated data will be available for analysis, but these same companies and institutions need to be aware of the importance of data collection and how they could benefit from them.