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Look into the future of the African city

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How do we identify the impact and trends resulting from urbanisation? What new regulation and governance models are needed? These are questions we need to answer in order to see what the future African city looks like, writes RIAAN GRAHAM, of Ruckus, sub-Saharan Africa.

What does the future African city look like? How do we identify the impact and trends resulting from urbanisation? What new regulation and governance models are needed? What about engagement models that embrace social inclusion and civic participation? These are all questions we need to answer and as 31 October marks World Cities Day – a day to promote successes and challenges resulting from urbanisation – the spotlight is on the future of cities.

The theme this year is ‘Innovative Governance, Open Cities’ which highlights the important role of urbanisation as a source of global development and social inclusion. What’s more, it is evident that innovative technologies and connectivity is critical during the planning, design, delivery and operation of smart infrastructure and services for urbanisation.

Around the world, cities are becoming more connected, collecting data everywhere to help planners make smarter decisions and deliver new services. The Internet of Things (IoT) is gaining traction, impacting every area of our lives and quickly turning “Smart Cities” from intangible visions of the future into a reality.

However, before Africa is able to start meeting those demands, we need to plan for capacity and speed to ensure a high-quality experience. What’s more, we need to take our unique challenges as a continent into account. A robust wireless network is a key part of this preparation – it is the “glue” that holds smart cities together, enabling effortless sharing of workloads with datacentres and bridging connectivity across wired and wireless.

So, what does the future African city look like?

Bridging the digital divide

As technology continues to advance at a rapid pace, the vision of the future is still emerging and we have yet to see what a true smart city will look like. Smart City IoT is an evolving concept, with lots of ideas but only a few complete deployments. Wi-Fi is the platform that will provide the foundation for smart city success, as it has immediate applications and can effectively connect a vast range of wireless technologies that will be involved in creating smart cities.

Smart cities will help address the economic and social inequality that this divide creates, by providing Internet access to all citizens. With robust networks in place, bridging this divide will help bring communities closer together and encourage citizens to play a more active role to local councils. Flawless connectivity will improve city infrastructure and make it possible for citizens to engage with their community, such as removing the roadblocks that complicate access to local services.

Business 

Revenue-generating applications will transform the way African businesses in smart cities communicate with their customers. In addition to an increased use of digital signage, to communicate offers and promotions, we can expect to see an increased use of beacons, which send notifications to customers’ smartphones as they enter a store. It will also transform the way people work and tech-savvy commuters will benefit from smart city technology to work on-the-go.

Smart utilities

In a smart city, lighting will automatically be switched off when it isn’t needed. It will be able to detect when people are on the street and turn on and off accordingly, reducing energy waste which is critical in countries where power is scare or expensive. In the near future, we can expect to see more city planners equipping their streets with smart lighting that uses sensors to track when there is high or low public footfall which will go a long way to reducing usage. Future smart traffic management is also likely to be a core feature of smart cities. This includes centrally-controlled traffic sensors and signals automatically regulating the flow of traffic in response to real-time demand, with the aim of smoothing flows of traffic to reduce congestion. This can go a long way to reduce traffic in high-dense areas over peak times like Sandton for example. And just think about the possibilities it could offer cities such as Lagos or Nairobi.

New technologies will also play an important role to help cities of the future promote sustainable energy use. For example, “smart bins” that alert collectors when they need to be emptied are being used today and we can expect to see more of them crop up in cities across the world as they embrace smart technology.

However, before becoming truly “smart”, cities need to implement the networks that will enable them to deploy new technology and the opportunities that Wi-Fi presents are simply too significant to ignore. The likes of Kenya, Nigeria, Zambia, and even Zimbabwe to name a few have embarked on wireless initiatives designed to bring better connectivity to more citizens. And other African countries are following suit. One key challenge lies in selecting the correct partner to work closely with them to identify and meet all their Wi-Fi needs. The right network will enable a city to save money through increased efficiency (for example, smart traffic and energy systems, as well as optimal budget allocation) and generate additional revenue, by encouraging visitors to return, businesses to invest and people to take up residency.

Africa has started using ICT investment to power its economy to gain more benefits. Government and the private sector are working together to fast track this process. Ultimately, when connectivity is improved, all stakeholders start drawing advantage from it. We are already seeing significant foreign direct investment into key ICT initiatives across the continent. So, even though mobility has sparked the flame around access, it will be wireless that fuels it into the digital future.

Here’s to the cities of the future!

Africa News

Smart grids needed for Africa’s utilities

Power utilities across Africa should rethink their business models and how they manage and monetise their assets to keep pace with the changing energy ecosystem, says COLIN BEANEY, Global Industry Director for Asset-intensive and Energy and Utilities at IFS.

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Africa’s abundant natural resources and urgent need for power mean that it is one of the most exciting and innovative energy markets in a world that is moving rapidly towards clean, renewable energy sources. The continent’s energy industry is taking new approaches to providing unserved and underserved communities with access to power, with an emphasis on smart technologies and greener energy sources.

Power systems are evolving from centralised, top-down systems as interest in off-grid technology grows among African businesses and consumers. And according to PwC, we will see installed power capacity rise from 2012’s 90GW to 380GW in 2040 in sub-Saharan Africa. Power utilities are needing to rethink their business models and how they manage and monetise their assets to keep pace with the changing energy ecosystem.

Energy and utilities providers are transforming from centralised supply companies to more distributed, bi-directional service providers. They can only achieve this through the evolution of “smart grids” where sensors and smart meters will be able to provide the consumer with a more granular level of detail of power usage. This shift from an energy supplier to “lifestyle provider” will require a much more dynamic and optimised approach to maintenance and field service.

African companies must thus embrace digital transformation as an imperative. This transformation begins by embracing enterprise asset management to improve asset utilisation. The subsequent steps are enhancing upstream and downstream supply chain management; resource optimisation; introducing enterprise operational intelligence; embracing new technologies such as the Internet of Things, machine learning, and predictive maintenance; and becoming a smart utility.

Embracing mobility to drive ROI

Getting it right is about putting in place an enterprise backbone that accommodates asset and project management, multinational languages and currencies, new energies and markets, visualisation of the entire value chain, and mobility apps. Mobile technologies that support the field workforce have a vital role to play in driving better ROI from utilities’ investments in enterprise asset management and enterprise resource planning solutions.

Today’s leading enterprise asset management solutions feature powerful functionality for mobile management of the complete workflow of work orders – from logging status changes and updates, from receiving and creating new orders to concluding the job and reporting time, material and expenses. Such solutions are easy to deploy and intuitive for end users to learn and use.

Importantly for organisations operating in parts of the continent with poor telecoms infrastructure, connectivity is not an issue. The solutions work offline and synchronises when network connectivity is available. Users can work on any device—laptops, tablets, and smartphones—commercial or ruggedised.

By ensuring that field technicians have easy access to information and processes, the mobile solution enables technicians and maintenance engineers to easily do the following tasks:

·         Create a new work order on the fly and log new opportunities

·         Access both historical and planned work information when requested

·         Permit customers to sign when the job is completed

·         Capture measurements and inspection notes on route work orders

·         Create new fault reports on routing

·         Facilitate documentation through photo capturing

·         Provide easy access to technical data and preventive actions.

The power of mobility allows the engineer to be the origin of all data capture on a service event. They can easily inquire on asset history, record parts used or parts needed for repair, record labour hours, and expenses as they occur, and any notes of repairs performed. When coupled with workforce management tools, such solutions unlock significant productivity gains for utilities who are trying to get the most from their workforce and assets.

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How machine learning can save your life

Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.

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Over 11000 people died during the 2014-2016 Ebola outbreak in West Africa.The virus hopped between Guinea, Leone, Nigeria and Liberia, before making its way to the UK and US. But what would have happened if analysis and machine learning stepped in to help solve the problem, asks ANESHAN RAMALOO of SAS.

But what if we could have predicted the outbreak months before it happened, buying us time to take proactive measures to contain it and curb its spread?

With access to overwhelming volumes of data, the computational power needed to store and analyse this data in real time, and sophisticated algorithms that can find patterns in the data and alert authorities to health problems before they become, well, problems, pandemics don’t have to be as devastating as they have been in the past.

In fact, with advanced data analytics, we can better manage any disease – long-term, short-term or pandemic – resulting in better patient treatment, more efficient use of resources and cost savings.

It’s been done before.

By analysing data from social media, blogs, online forums and keyword searches, we were able to predict the 2012-2013 US flu season three months before the Center for Disease Control (CDC) issued its first official warning.

Imagine the impact if the same analytical power was applied across the entire healthcare spectrum – not only on a national and global level, but right down to the individual level.

Data evolution

In the past, health workers relied on manually intensive, paper-based systems to record infections and deaths during disease outbreaks. Not only was it easy for errors to slip through but because the data was anecdotal and historical, authorities did not get a complete understanding of the reach and impact of the outbreak.

During the Ebola outbreak, the CDC adopted a mobile data collection system that enabled health workers to instantly submit information to a database via text messages. This low-cost method of information gathering not only resulted in fewer errors but also allowed analysts to draw up detailed maps of population movements, which made it easier to understand how the disease was likely to spread, and where to set up treatment centres.

While this was certainly an improvement on the paper-based systems of old, the drawback was that mobile data was historic and did not provide researchers with the ability to track developments and population movements in real time.

Data-driven action

But mobile phones are just one source of data. Today, health authorities can overlay thousands of data sources – including social media, health and physician reports, keyword searches, media reports, transactional data from retailers and pharmacies, airline ticket sales, geospatial data and more – to not only better manage diseases and outbreaks when they do happen, but to see them coming months in advance – and what could happen if we don’t act on the information.

By mining structured and unstructured data, we can track the movements of infected populations and who they come into contact with; we can measure the success of containment policies, education campaigns and treatments – and what to do if they’re not working; we can determine the effect of weather and other environmental factors on the spread of diseases.

Never before have we been able to act on information to save lives, not just during pandemics but through better understanding and treatment of diseases.

Personalised treatment

Until now, standard treatments for diseases such as cancer and HIV have been applied to all patients, regardless of their unique profiles and with little understanding as to why some people respond well to certain treatments and others don’t.

But by analysing and creating ‘medical maps’ of individuals that take into account their anatomy, physiology, DNA, RNA and chemical composition, doctors can prescribe personalised treatments that have a greater chance of success.

There are many other benefits of data analysis in healthcare:

·        Personalised treatment can result in fewer hospital admissions and can produce faster results and better experiences for patients;

·        By better understanding the impact of lifestyle and diet on health, medical aid providers can educate their members with the aim of improving their health, which could result in cost savings for both the provider and the member;

·        Governments can use data to develop proactive approaches to protecting and promoting public health, to prioritise services and to find ways to cut costs so that they can provide healthcare to more citizens.

·        By sharing data and results from clinical trials and combining that data with academic, patient and industry data, medical researchers can better understand the genetics of viruses, why some strains are more deadly than others, and why some people are more resistant to viruses. This could spark innovation and generate new insights that ultimately improve treatment and outcomes.

AI and machine learning

As the use of intelligent algorithms, machine learning and natural language processing becomes more entrenched in advanced data analytics, technology will increasingly supplement the skills of humans to produce faster and more accurate medical diagnoses.

We’re already seeing successful applications of artificial intelligence (AI) in predicting relapse in leukaemia patients and in distinguishing between different types of cancer.

Machine learning can extract valuable insights from unstructured data like clinical notes and academic journals to provide even larger datasets that will transform the medical industry into a proactive front against diseases.

There are plenty of doomsday theories about how machines will supersede our intelligence and rise against us. But there aren’t enough stories about the potential of data analytics, AI and machine learning to supplement human skills and knowledge to drastically changes lives for the better – and even save them. Right now, it’s looking more likely that machines will actually help us to live longer – and I don’t know many people who would object to that.

 

  • ANESHAN RAMALOO, ‎Data Scientist and Senior Business Solutions Manager at SAS.
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