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Project Bloodhound ready for South Africa

The quest to break the world land speed record is a long and winding road that leads to South Africa – and is designed to inspire school kids everywhere with a love of science and technology, writes ARTHUR GOLDSTUCK

There can be few more desolate places in the world than Hakskeen Pan, a flat, endless dried-out lake bed in South Africa’s Northern Cape province, near the border with Botswana and Namibia.

But that is precisely what has propelled it into the international spotlight. It is one of the few places in the world that is isolated enough, flat enough, and with the right terrain to support a bold quest.

The crust of the lake bed at Haksteen Pan is ideal for an attempt not only on the world landspeed record, but for the first land vehicle to travel at 1 600 kilometres per hour. Project Bloodhound will stretch the limits of a vehicle on wheels far beyond what was ever thought possible.

The man behind the project, the crusty British racing veteran Richard Noble, is no stranger to absurdly extreme feats like this.

“We’ve got a long history of doing it,” he said in an interview last week. “I broke the world land speed record in 1983. After that, we were up against the Americans to achieve the first ever supersonic ride in 1997, and we succeeded. In this case, we’re increasing the land speed record by a whopping 30%, and we’re convinced we can do it.”

The pilot will be Andy Green, but a vast team of engineers, researchers and other specialists has come together in pursuit of the vision.

Bloodhound pilot Andy Green Photo courtesy Project Bloodhound

Bloodhound pilot Andy Green
Photos courtesy Project Bloodhound

“We’ve gone through a very difficult phase,” he said. “The weakness of a project like this is the finances. It’s a long-term project because of its considerable investment in terms of engineering. There have been a whole lot of financial setbacks, but the team has held together. In a lesser organisation people would have just walked, but they’ve absolutely stuck together.”

In the next two weeks, the car will go through its most critical test yet.

“We’ve got to get the car into what we call runway form, and where we work in Bristol is unsuitable for running a jet engine. So we will be running it in Newquay in Cornwall to prove that the car works and runs, but at this stage we will go no faster than 200 miles per hour.”

Part of the challenge is that the project is no longer only about engineering, as it was back in 1983 and 1997.

Photo courtesy Project Bloodhound

This time round, it remains as important, but is joined by technology that had barely arrived back then: the Internet, high-speed mobile connectivity, database software, and a wide variety of environmental sensors.

This combination means that the Bloodhound SSC (for supersonic car) will produce a massive amount of data that will be accessible instantly, worldwide. And that, in turn, will be used for one of the most ambitious global attempts inspire schoolchildren to want to learn about the STEM subjects: Science, Technology, Engineering and Mathematics.

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The car is being built and tested in the United Kingdom, but the project depends on Hakskeen Pan.

While the terrain provided the needed long, flat landscape and the right surface, it was also littered with rocks and stones. So the first essential piece of work was to clear the area by hand. The local Mier community was employed to do the job. Last year, the Federation Internationale de l’Automobile (FIA) presented certificates of recognition to over 300 members of the community for “the largest area of land ever cleared by hand for a motorsports activity”. They had removed 16 000 tonnes of rock from 22 million square metres of dry lake bed.

Project Bloodhound announced: “Their amazing work has been a vital part of building the world’s fastest race track and means that next year Andy Green can drive Bloodhound SSC at over 1400kph in Northern Cape, South Africa, without worrying about a single stray rock damaging the Car.”

The attempt, set for 2018, should have been made during 2017, but ran into a hitch and, Noble admitted in an interview last week, it was not a technical one. He had just presented a keynote address on the project at Oracle OpenWorld, a massive annual conference in San Francisco, where more than 60 000 people come to learn about the latest offerings from global database software giant Oracle. The company had already committed to providing the technology platform needed to share the car’s massive data output with the world.

Bloodhound Project director Richard Noble

Bloodhound Project director Richard Noble

At the event, Oracle’s president of product development, Thomas Kurian, announced that the company’s educational arm, Oracle Academy, would partner with Project Bloodhound to popularise STEM subjects.

“Effectively, Oracle is educating the world,” said Noble. “The idea came from the US manned space programme. When you study what happened with the Apollo programme, you see this enormous growth in the emergence of scientists, engineers and mathematicians as a result of interest in space flight.

“We were working so hard taking project Bloodhound forward, we didn’t have time to look over shoulder to see what we’d achieved. We asked the University  of Swansea, which is working with us on the aerodynamics of Bloodhound, for a letter telling us what had happened as a result of the project.

“They said their engineering applications and intake were up 150% directly as a result of their work on Bloodhound. Intake of aerodynamics students was up 350%. The value of Bloodhound, to them, was 5-million pounds every year. Kids were coming from the USA to study at Swansea.”

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Another research partner in the project, the University of Western England, saw even greater benefit: they valued the benefits of their work on Bloodhound over ten years at 77-million pounds.

“We were staggered. We had no idea this was the scale of what we were doing. The STEM education system had all but collapsed and the kids all wanted to be singers and dancers. They saw physics as impossible and teachers were really struggling. Inspiring children is the unique selling proposition of Project Bloodhound.”

See: Making Project Bloodhound possible

  • Arthur Goldstuck is founder of World Wide Worx and editor-in-chief of Gadget.co.za. Follow him on Twitter on @art2gee and on YouTube.

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Now IBM’s Watson joins IoT revolution in agriculture

Global expansion of the Watson Decision Platform taps into AI, weather and IoT data to boost production

IBM has announced the global expansion of Watson Decision Platform for Agriculture, with AI technology tailored for new crops and specific regions to help feed a growing population. For the first time, IBM is providing a global agriculture solution that combines predictive technology with data from The Weather Company, an IBM Business, and IoT data to help give farmers around the world greater insights about planning, ploughing, planting, spraying and harvesting.

By 2050, the world will need to feed two billion more people without an increase in arable land [1]. IBM is combining power weather data – including historical, current and forecast data and weather prediction models from The Weather Company – with crop models to help improve yield forecast accuracy, generate value, and increase both farm production and profitability.

Roric Paulman, owner/operator of Paulman Farms in Southwest Nebraska, said: “As a farmer, the wild card is always weather. IBM overlays weather details with my own data and historical information to help me apply, verify, and make decisions. For example, our farm is in a highly restricted water basin, so the ability to better anticipate rain not only saves me money but also helps me save precious natural resources.”

New crop models include corn, wheat, soy, cotton, sorghum, barley, sugar cane and potato, with more coming soon. These models will now be available in the Africa, U.S. Canada, Mexico, and Brazil, as well as new markets across Europe and Australia.

Kristen Lauria, general manager of Watson Media and Weather Solutions at IBM, said: “These days farmers don’t just farm food, they also cultivate data – from drones flying over fields to smart irrigation systems, and IoT sensors affixed to combines, seeders, sprayers and other equipment. Most of the time, this data is left on the vine — never analysed or used to derive insights. Watson Decision Platform for Agriculture aims to change that by offering tools and solutions to help growers make more informed decisions about their crops.” 

The average farm generates an estimated 500,000 data points per day, which will grow to 4 million data points by 2036 [2]. Applying AI and analysis to aggregated field, machine and environmental data can help improve shared insights between growers and enterprises across the agriculture ecosystem. With a better view of the fields, growers can see what’s working on certain farms and share best practices with other farmers. The platform assesses data in an electronic field record to identify and communicate crop management patterns and insights. Enterprise businesses such as food companies, grain processors, or produce distributors can then work with farmers to leverage those insights. It helps track crop yield as well as the environmental, weather and plant biologic conditions that go into a good or bad yield, such as irrigation management, pest and disease risk analysis and cohort analysis for comparing similar subsets of fields.

The result isn’t just more productive farmers. Watson Decision Platform for Agriculture could help a livestock company eliminate a certain mold or fungus from feed supply grains or help identify the best crop irrigation practices for farmers to use in drought-stricken areas like California. It could help deliver the perfect French fry for a fast food chain that needs longer – not fatter – potatoes from its network of growers. Or it could help a beer distributor produce a more affordable premium beer by growing higher quality barley that meets the standard required to become malting barley.

Watson Decision Platform for Agriculture is built on IBM PAIRS Geoscope from IBM Research, which quickly processes massive, complex geospatial and time-based datasets collected by satellites, drones, aerial flights, millions of IoT sensors and weather models. It crunches large, complex data and creates insights quickly and easily so farmers and food companies can focus on growing crops for global communities.

IBM and The Weather Company help the agriculture industry find value in weather insights. IBM Research collaborates with start up Hello Tractor to integrate The Weather Company data, remote sensing data (e.g., satellite), and IoT data from tractors. IBM also works with crop nutrition leader Yara to include hyperlocal weather forecasts in its digital platform for real-time recommendations, tailored to specific fields or crops. IBM acquired The Weather Company in 2016 and has since been helping clients better understand and mitigate the cost of weather on their businesses. The global expansion of Watson Decision Platform for Agriculture is the latest innovation in IBM’s efforts to make weather a more predictable business consideration. Also just announced, Weather Signals is a new AI-based tool that merges The Weather Company data with a company’s own operations data to reveal how minor fluctuations in weather affects business.

The combination of rich weather forecast data from The Weather Company and IBM’s AI and Cloud technologies is designed to provide a unique capability, which is being leveraged by agriculture, energy and utility companies, airlines, retailers and many others to make informed business decisions.

[1] The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”

[2] Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10


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What if Amazon used AI to take on factories?

By ANTONY BOURNE, IFS Global Industry Director for Manufacturing

Amazon recently announced record profits of $3.03bn, breaking its own record for the third consecutive time. However, Amazon appears to be at a crossroads as to where it heads next. Beyond pouring additional energy into Amazon Prime, many have wondered whether the company may decide to enter an entirely new sector such as manufacturing to drive future growth, after all, it seems a logical step for the company with its finger in so many pies.

At this point, it is unclear whether Amazon would truly ‘get its hands dirty’ by manufacturing its own products on a grand scale. But what if it did? It’s worth exploring this reality. What if Amazon did decide to move into manufacturing, a sector dominated by traditional firms and one that is yet to see an explosive tech rival enter? After all, many similarly positioned tech giants have stuck to providing data analytics services or consulting to these firms rather than genuinely engaging with and analysing manufacturing techniques directly.

If Amazon did factories

If Amazon decided to take a step into manufacturing, it is likely that they could use the Echo range as a template of what AI can achieve. In recent years,Amazon gained expertise on the way to designing its Echo home speaker range that features Alexa, an artificial intelligence and IoT-based digital assistant.Amazon could replicate a similar form with the deployment of AI and Industrial IoT (IIoT) to create an autonomously-run smart manufacturing plant. Such a plant could feature IIoT sensors to enable the machinery to be run remotely and self-aware; managing external inputs and outputs such as supply deliveries and the shipping of finished goods. Just-in-time logistics would remove the need for warehousing while other machines could be placed in charge of maintenance using AI and remote access. Through this, Amazon could radically reduce the need for human labour and interaction in manufacturing as the use of AI, IIoT and data analytics will leave only the human role for monitoring and strategic evaluation. Amazon has been using autonomous robots in their logistics and distribution centres since 2017. As demonstrated with the Echo range, this technology is available now, with the full capabilities of Blockchain and 5G soon to be realised and allowing an exponentially-increased amount of data to be received, processed and communicated.

Manufacturing with knowledge

Theorising what Amazon’s manufacturing debut would look like provides a stark learning opportunity for traditional manufacturers. After all, wheneverAmazon has entered the fray in other traditional industries such as retail and logistics, the sector has never remained the same again. The key takeaway for manufacturers is that now is the time to start leveraging the sort of technologies and approaches to data management that Amazon is already doing in its current operations. When thinking about how to implement AI and new technologies in existing environments, specific end-business goals and targets must be considered, or else the end result will fail to live up to the most optimistic of expectations. As with any target and goal, the more targeted your objectives, the more competitive and transformative your results. Once specific targets and deliverables have been considered, the resources and methods of implementation must also be considered. As Amazon did with early automation of their distribution and logistics centres, manufacturers need to implement change gradually and be focused on achieving small and incremental results that will generate wider momentum and the appetite to lead more expansive changes.

In implementing newer technologies, manufacturers need to bear in mind two fundamental aspects of implementation: software and hardware solutions. Enterprise Resource Planning (ERP) software, which is increasingly bolstered by AI, will enable manufacturers to leverage the data from connected IoT devices, sensors, and automated systems from the factory floor and the wider business. ERP software will be the key to making strategic decisions and executing routine operational tasks more efficiently. This will allow manufacturers to keep on top of trends and deliver real-time forecasting and spot any potential problems before they impact the wider business.

As for the hardware, stock management drones and sensor-embedded hardware will be the eyes through which manufacturers view the impact emerging technologies bring to their operations. Unlike manual stock audits and counting, drones with AI capabilities can monitor stock intelligently around production so that operations are not disrupted or halted. Manufacturers will be able to see what is working, what is going wrong, and where there is potential for further improvement and change.

Knowledge for manufacturing

For many traditional manufacturers, they may see Amazon as a looming threat, and smart-factory technologies such as AI and Robotic Process Automation (RPA) as a far off utopia. However, 2019 presents a perfect opportunity for manufacturers themselves to really determine how the tech giants and emerging technologies will affect the industry. Technologies such as AI and IoT are available today; and the full benefits of these technologies will only deepen as they are implemented alongside the maturing of other emerging technologies such as 5G and Blockchain in the next 3-5 years. Manufacturers need to analyse the needs which these technologies can address and produce a proper plan on how to gradually implement these technologies to address specific targets and deliverables. AI-based software and hardware solutions will fundamentally revolutionise manufacturing, yet for 2019, manufacturers just have to be willing to make the first steps in modernisation.

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