The question posed to the students was: “What are the supply and demand factors affecting the Cape Town water crisis?”
Using publicly available data, they showed that the blame cannot be attributed to any single cause, but that multiple factors in varying degrees each contributed to the water crunch.
The students concluded that a combination of low rainfall, population growth, shifting consumption levels as well as evaporation, were all factors affecting the City’s critical dam levels.
The project was the first to be set by the Academy, and was handed to the first intake of 100 students on their first day at the Academy in January this year. They were given two months to work on the problem, with the EDSA supporting them with the necessary skills to tackle the problem.
“In essence, data science is about taking real world problems and finding real world solutions,” said Aidan Helmbold, co-founder of the EDSA.
“The water project required our interns to make use of various available data sets and technology to analyse the City’s water consumption, and to make these insights available so that the City could better understand the underlying dynamics,” Helmbold added.
Students had to analyse the main supply and demand factors affecting the water crisis. Demand side factors were drawn from water consumption data available on the City of Cape Town’s Open Data portal.
On the supply side, factors such as dam levels, and the impact of weather data, such as rainfall, temperature and windfall patterns on water evaporation, were considered.
Analysis of water demand also took into consideration population figures from the 2011 census, the impact of water leaks as well as usage from sources other than households, such as industries and farms.
“I think the most astounding aspect for us as education providers was to see how much 100 young minds can achieve with only three months of data science training behind them,” Helmbold said.
“We were also amazed at how quickly the students were able to adapt to the softer skills, such as teamwork and the realities of managing multiple project deliverables.”
“Many of these young people come from very humble circumstances and have only a matric to their name. Yet they have demonstrated through the project, their ability to get to grips with complex problems and to come up with life-ready solutions to them. ”
The EDSA will present the data finds to City of Cape Town officials early in June.
“Ideally, the EDSA would like to partner with the city to contribute to deepening the understanding of the role of data and the value its insights can bring to the decision making process,” Helmbold said.
CoCT and CiTi’s #newnormal – Cape Town Water Saving Design Sprint
In a separate but related endeavour, the Cape Innovation and Technology Initiative (CiTI) together with the City of Cape Town, recently held a weekend-long hackathon to come up with solutions that would engage and encourage Capetonians to continue to save water and remain conscious of their water habits.
In order to address this challenge, a two-day design sprint was held at the Woodstock Bandwidth Barn. Participants were given the challenge to ‘Design a digital campaign, tool, game or app which will help make water-saving the new normal’.
Drawing on the City’s Open Data portal, this event challenged teams to come up with ideas on how to use technology to motivate long-term behavioural change regarding water saving and to propose solutions that were relevant to the wider community. Participants were also briefed by Green Cape and behavioural design professionals.
The aim of the user-centred design hackathon was to bring together people from diverse backgrounds, experiences and skill sets. About 60 members of the public including 30 of the EDSA’s interns were involved in the design sprint.
The weekend-long event was facilitated by experienced design thinking professionals who took teams through a structured process.
“This allowed people to participate in the event without already having a solution in mind, focusing rather on getting teams to understand the problem from a user perspective first,” said Michelle Matthews, Head of Innovation at CiTi.
This user-centred approach included having participants’ interview members of the public, to help participants propose solutions, which citizens might actually need and adopt.
One of the EDSA teams came up with an idea for a Sims-like game that tracked an individual’s water consumption rates, rewarding them with points for saving water and connecting them with others with similar household set-ups to benchmark usage and share tips. This team eventually came third in the event.
“We were delighted by the calibre of solutions that the teams demonstrated, which had the potential to be applied to one of the biggest issues facing the city,” Matthews said.
Motor Racing meets Machine Learning
The car of tomorrow, most of us imagine, is being built by the great automobile manufacturers of the world. More and more, however, we are seeing information technology companies joining the race to power the autonomous vehicle future.
Last year, chip-maker Intel paid $15.3-billion to acquire Israeli company Mobileye, a leader in computer vision for autonomous driving technology. Google’s autonomous taxi division, Waymo, has been valued at $45-billion.
Now there’s a new name to add to the roster of technology giants driving the future.
Amazon Web Services, the world’s biggest cloud computing service and a subsidiary of Amazon.com, last month unveiled a scale model autonomous racing car for developers to build new artificial intelligence applications. Almost in the same breath, at its annual re:Invent conference in Las Vegas, it showcased the work being done with machine learning in Formula 1 racing.
AWS DeepRacer is a 1/18th scale fully autonomous race car, designed to incorporate the features and behaviour of a full-sized vehicle. It boasts all-wheel drive, monster truck tires, an HD video camera, and on-board computing power. In short, everything a kid would want of a self-driving toy car.
But then, it also adds everything a developer would need to make the car autonomous in ways that, for now, can only be imagined. It uses a new form of machine learning (ML), the technology that allows computer systems to improve their functions progressively as they receive feedback from their activities. ML is at the heart of artificial intelligence (AI), and will be core to autonomous, self-driving vehicles.
AWS has taken ML a step further, with an approach called reinforcement learning. This allows for quicker development of ML models and applications, and DeepRacer is designed to allow developers to experiment with and hone their skill in this area. It is built on top of another AWS platform, called Amazon SageMaker, which enables developers and data scientists to build, train, and deploy machine learning quickly and easily.
Along with DeepRacer, AWS also announced the DeepRacer League, the world’s first global autonomous racing league, open to anyone who orders the scale model from AWS.
As if to prove that DeepRacer is not just a quirky entry into the world of motor racing, AWS also showcased the work it is doing with the Formula One Group. Ross Brawn, Formula 1’s managing director of Motor Sports, joined AWS CEO Andy Jassy during the keynote address at the re:Invent conference, to demonstrate how motor racing meets machine learning.
“More than a million data points a second are transmitted between car and team during a Formula 1 race,” he said. “From this data, we can make predictions about what we expect to happen in a wheel-to-wheel situation, overtaking advantage, and pit stop advantage. ML can help us apply a proper analysis of a situation, and also bring it to fans.
“Formula 1 is a complete team contest. If you look at a video of tyre-changing in a pit stop – it takes 1.6 seconds to change four wheels and tyres – blink and you will miss it. Imagine the training that goes into it? It’s also a contest of innovative minds.”
Formula 1 racing has more than 500 million global fans and generated $1.8 billion in revenue in 2017. As a result, there are massive demands on performance, analysis and information.
During a race, up to 120 sensors on each car generate up to 3GB of data and 1 500 data points – every second. It is impossible to analyse this data on the fly without an ML platform like Amazon SageMaker. It has a further advantage: the data scientists are able to incorporate 65 years of historical race data to compare performance, make predictions, and provide insights into the teams’ and drivers’ split-second decisions and strategies.
This means Formula 1 can pinpoint how a driver is performing and whether or not drivers have pushed themselves over the limit.
“By leveraging Amazon SageMaker and AWS’s machine-learning services, we are able to deliver these powerful insights and predictions to fans in real time,” said Pete Samara, director of innovation and digital technology at Formula 1.
LG rethinks portable speakers
LG adds three sizes to its XBoom Go portable speaker line in a portable revision, writes BRYAN TURNER.
Portable Bluetooth speakers are fairly commonplace at a pool party because they’re battery-powered. The only issue is that louder speakers usually distort the music or break the bank. The LG XBoom aims to change this.
LG has partnered with Meridian Audio to produce great sounding speakers that can go loud without distorting the audio. Meridian Audio is an expert in high-performance, high-fidelity audio experiences. The company is best known for producing the industry’s first audiophile-quality compact disc player and provide audio equipment to McLaren and Jaguar Land Rover.
The Bluetooth software in the XBoom Go is Qualcomm aptX HD compatible, meaning that 24bit vinyl-quality audio can be played through this speaker over Bluetooth instead of standard-fidelity audio.
The major phone assistants feature on these speakers, with tethered Google Assistant or Apple Siri functionality from one’s smartphone. This makes it very convenient to use the voice assistant button to skip tracks and change music when one’s hands are wet.
Three models of the XBoom Go series – the PK3, PK5 and PK7 – offer different audio functions depending on the audio needs of the user. Best fits for these speakers are:
PK3 – The Pool Friendly Speaker: The PK3 is IPX7 water resistant, up to 1 metre for 30 minutes, making this speaker accident proof at pool parties. Boasting up to 12 hours of playback from its built-in battery, this speaker will last as long as the party.
PK5 – The Party Friendly Speaker: Even if the lunch braai turns into a midnight feast, this speaker will play throughout as its battery lasts up to 18 hours. Clear Vocal technology is added to the PK5, which reduces audio imperfections from the music for a sharper sound. It is also water and splash resistant and has a handle, allowing for it to be easily carried. Built-in LED lights which pulse with the beat of the music on this speaker provide a light show for any song.
PK7 – The Audiophile’s Speaker: With a battery life that lasts for up to 22 hours, the PK7 also contains an LED light to the rhythm of the sound. The speaker integrates a convenient handle grip that allows for it to be transported securely. The powerful PK7 Bluetooth speaker also distributes its high frequencies across two separate tweeters for more precise sonic detail.
Overall, LG’s XBoom PK portable speakers are a phenomenal set of high-quality wireless speakers.