Christopher Sciacca takes you on a developer’s tour of IBM Research projects in the labs in Kenya and South Africa. See how IoT, Watson, blockchain, data analytics, and security will transform the continent’s infrastructure.

In this video:

Chris Sciacca, Communications Manager for IBM Research Labs in Europe, wants to take you on a tour of IBM Research projects in the labs in Kenya and South Africa. All the projects in the African labs, like the projects in IBM Research Labs worldwide, fall into one of these four strategic imperatives categories:

  • Reimagining computing
  • Developing core AI
  • Transforming industries through science and AI
  • Defining and optimizing blockchain

Digital urban ecosystems

IBM scientists are discovering ways to use cognitive systems, data analytics, IoT, and other technologies to improve life in urban environments.

Air pollution
Building on IBM’s global Green Horizons initiative and using machine learning and cognitive models help uncover greater insight about the nature and causes of air pollution and model the effectiveness of intervention strategies, researchers work closely with experts from South Africa’s Council for Scientific and Industrial Research to analyze historical and real-time data from environmental monitoring stations. The project has recently been extended to predict ground level ozone and air quality forecasting.

Traffic optimization
Traffic congestion costs Johannesburg commuters an extra 35 minutes of travel time each day and much of this comes from an unreliable traffic light infrastructure, resulting from scheduled power cuts and vandalism. Using real-time anonymized traffic data from TomTom combined with Twitter, IBM scientists have developed a traffic optimization recommendation tool which can help city officials dispatch volunteer traffic cops, known locally as “pointsmen,” to the intersections where they are most urgently needed.

Fire incidence risk and severity
Due to its unique topography and surrounds of fire-dependant and fire-prone vegetation, wildfires are a problem for Cape Town. Using data from The Weather Company and city’s Open Data portal containing vegetation, topographic, and fire incidence data, IBM scientists have developed a cognitive dashboard which can assess fire incidence risk and severity to help officials raise public awareness and prepare for emergency response.

Develop a new solar recommendation app
The number of people living off-the-grid in Africa has grown by 114 million since 2000. To help meet the energy needs of these communities who are often in remote settlements or who would like to make use of renewable energy, IBM scientists have developed a new solar recommendation app that applies analytics to recommend a photovoltaic system design and component sizing (for solar panels, inverters, charge controllers) based on their energy needs and the solar irradiance from IoT at their particular location.

Dr. Bonolo Mathibela is working towards developing crisis management systems that positively impact society. She leads the lab’s efforts in Intelligent Transport Systems and is developing an autonomous platform for reducing traffic congestion in resource constrained environments.

Developers can try cognitive modeling in this hands-on recipe: How to Teach a Cognitive Engine.
Developers can try optimizing data in this hands-on recipe: Analyze device data using IBM Data Science Experience.
Developers can try a predictive app in this hands-on recipe: Predictive Maintenance Solution for Electric Engines.
Developers can try mobile app development in this hands-on recipe: A generic framework for developing and unit testing CRUD applications.

Next generation public sector

Governments play a critical role in the growth and sustainable development of the economies of Africa and with the right amount of big data solutions, advanced analytics, and cloud technologies, they can make better decisions. IBM Research, using state-of-the-art cognitive analytics and tools, intends to enable local governments to identify bottlenecks in processes and improve the outcome of decisions.

One example is the annual World Bank ease-of-business ratings – some African governments are using IBM insights to help improve their score on this system. In one case study, analysis indicated that the amount of paperwork required to open a business was overwhelming, so the government reduced the paperwork to a single, more simple form. Dr. Charity Wayua took her skills in biological systems and applied them to government processes, using artifact-centric process modeling, a methodology which collects and analyzes data that would support or refute a hypothesis developed by the team.

Developers can try insight generation in this hands-on recipe: Analyzing sentiments in news.

Data-driven healthcare

IBM scientists are discovering ways to use cognitive systems, data analytics, IoT, and other technologies to improve healthcare.

Anonymously trace tuberculosis spread with fashion wearables
IBM scientists are designing fashionable and durable bracelets and hairbands embedded with passive RFID tags connected to Watson IoT to anonymously trace how tuberculosis spreads in cities and rural areas. This innovation will help healthcare organizations develop prevention strategies, enable public health officials to respond effectively, and hospitals to prepare for emergencies.

Transform cancer reporting, prevention and precision medicine with cognitive systems
In a proof-of-concept study, IBM scientists have discovered a basic molecular link between cancer causing genes and those associated with metastasis, the cause of 90 percent of cancer related deaths. Using anonymous, unstructured data, the team is developing cognitive algorithms to automate inference of national cancer statistics in South Africa and this innovation is expected to reduce a five-year time lag in cancer statistics reporting to a real-time schedule, while also integrating public health and precision medicine approaches to cancer care and treatment.

Predict and prepare for future disease outbreaks
IBM scientists collected 65 samples of microbes and bacteria from 19 bus stations across Johannesburg as part of the global metagenomics and metadesign subway design consortium effort. Once the samples are processed, the results will be available to city planners, public health officials, and scientists who will use the data to help officials predict and prepare for future disease outbreaks and discover new species and biological systems.

For example, Toby Kurien, an electronics engineer, is using smart sensors and IBM analytics to demonstrate how communicable diseases can spread. This will help healthcare organizations to develop prevention strategies, enable public health officials to respond more effectively, and hospitals better prepare for emergencies.

Developers can try sensors in this hands-on recipe: Integrate an air quality sensor.

Developers can try managing data in this hands-on recipe: Collect and discover IoT data. Or this one on data synchronization: Data synchronization between databases.

Developers can try a predictive app in this hands-on recipe: Predictive Maintenance Solution for Electric Engines.

Digital agriculture

Arable farming is big business in Kenya, but most farms are relatively small, lacking the size to take advantage of economies of scale. With unpredictable rainfall and variable water supplies, it is difficult for farmers to ensure crops are not under- or over-watered, but with the increasing levels of Internet access via smartphones and the affordability of modern sensors, tech-savvy farmers can change the way they run their businesses.

Dr. Kala Fleming, Water, Agriculture, and Health Manager, says:

“In Kenya alone, there are 15 million small-scale farmers. Most rely on aggregators to help get crops to market. We set out to empower farmers and investors with technology to help create a more sustainable farming industry. We place sensors at farms to capture data on water tank levels, soil moisture, and rates of photosynthesis and securely stream it to the IoT Foundation. There, an analytics engine within IBM Bluemix measures how the plants are doing and identifies patterns of water usage, then insights are provided back to the farmers via an app on a tablet or smart phone.”

She demonstrated a new solution called EZ Farm to help small-scale farmers to better manage their water resources. The researchers use big data and IoT technologies to help small scale farmers better manage water resources. EZ-Farm is a remote monitoring solution that helps farmers manage water and agricultural aggregators identify the best prospects for investment.

Dr. Fleming concludes:

“The potential for the solution is huge. For example, we are uncovering insights that can be used to improve government policy on subsidy distribution and groundwater management. The development of EZ-Farm enables a smarter approach to agriculture in Africa and beyond.”

Developers can try digitally enhanced farming in this hands-on recipe: Greenhouse Drought Warning System.
You can learn about mesh networking in this hands-on recipe: Publish to Watson IoT from your SmartMesh IP Network.

Inclusive financial services

IBM Research is dedicated to creating solutions to provide access to financial services for people and businesses that cannot access credit or may be located in remote areas by designing and helping to implement mobile payment system components. For example, M-Pesa is one mobile phone-based money transfer, financing, and microfinancing service, launched in 2007 by Vodafone for Safaricom and Vodacom. It allows users to deposit, withdraw, and transfer money and pay for goods and services easily with a mobile device.

Providing loans for people whose religious beliefs prohibit earning profit on interest (such as Muslims) is another task IBM Research is tackling using blockchain to help implement asset-based loan systems in which the lender buys the goods the applicant intends to purchase with the loan and resells the goods to the applicant at a higher price.

One way IBM Research has helped to extend financial inclusion besides more effective credit scoring methods and alternative lending platforms is through the use of blockchain to ensure transaction security and digital privacy protection.

Research Scientist Abdigani Diriye manages the Inclusive Financial Services Group, a team that works in the space of human-computer interaction, data-mining, and FinTech to design, develop and deploy novel solutions that combine human- and machine-generated data to support people in making sense of information and accessing services more easily, effectively and efficiently.

Developers can try blockchain in this hands-on recipe: Deploy a sample smart contract.

Exploring the universe

IBM scientists are using cognitive systems and advanced data analytics to explore the universe.

Develop unsupervised algorithms to explore space
In 2018 the Square Kilometer Array (SKA), the world’s largest radio telescope, will be built in South Africa and Australia and IBM researchers will be collaborating with SKA South Africa on the development of unsupervised algorithms which can make groundbreaking astronomical discoveries by revealing hidden structures and finding new types of objects such as pulsars, black holes, and quasars. Researchers expect to be able to apply this cognitive technology to other applications, including the development of new pharmaceuticals and genomics.

Analyze the radio events from SETI
IBM scientists in South Africa are joining NASA, the SETI Institute, and Swinburne University to develop an Apache Spark application to analyze the 168 million radio events detected over the past 10 years by the Allen Telescope Array. Considered the “ultimate big data challenge,” the complex nature of the data demands sophisticated mathematical models to tease out faint signals and machine learning algorithms to separate terrestrial interference from true signals of interest. These requirements are well suited to the scalable in-memory capabilities offered by Apache Spark when combined with the big data capabilities of the IBM Cloud and IBM Bluemix Spark.

Developers can try assembling an algorithm in Node-RED in this hands-on recipe: Parking IoT solution (Step 7).

Resources for you

Internet of Things

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