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Drones fly high in farming

The Association for Unmanned Vehicle Systems International estimates that farms will eventually account for an 80% share of the projected $127 billion commercial drone market, which is why a Cape Town start-up has already found ways to help farmers mange their land through drone photography and data analysis.

The Association for Unmanned Vehicle Systems International estimates that farms will eventually account for an 80% share of the projected $127 billion commercial drone market. By conceptualising, developing and building their own autonomous unmanned aerial vehicles (UAVs) and systems, a Cape Town start-up is already helping farmers manage their land through drone aerial photography and data analysis.

Founded by two engineers, James Paterson and Benji Meltzer who studied at the Massachusetts Institute of Technology (MIT) and Imperial College London respectively, the main focus of Aerobotics is to develop turnkey systems, which collect actionable data for their clients. This is an end-to-end drone solution that includes data processing, analysis software and support.

Paterson and Meltzer, both in their mid-20s, were top of their undergraduate class at the University of Cape Town. A few years later they reconnected and began to discuss starting a business together. Paterson had grown up on a farm in Clanwilliam in the Western Cape and had been inventing tools to assist in agricultural from as young as primary school. His passion for farming and engineering skills were perfectly suited to Meltzer’s strong talents in data collection and analysis.

“The drone space is growing quickly and it was the perfect opportunity to combine both our skillsets. We do everything in-house, from building and maintaining the drones to writing the software for them and processing data,” Meltzer explains.

Aerobotics, a seven-person company that recently acquired GIBS MBA graduate Andrew Burdock as its Commercial Director, currently focuses on the agricultural and mining spaces. It has a joint venture in place in Australia, contracts flowing in and is currently seeking funding partners as it expands in western markets.

With an American study showing that corn, soybean and wheat farmers could save an estimated $1.3 billion annually by using drones to increase crop yields and reduce input costs, the team is making steady progress in this sector. This is largely due to its affordability, ease-of-use and one-flight data versatility. The drones provide valuable data to the farmers, including determining where crops are under stress which helps to increase yields. “It’s all about early problem detection,” Paterson says, “Farmers can also use this data for reducing input costs by reducing both water and chemical usage.”

The Aerobotics drones are appealing in that they are entirely autonomous, which means that the user simply has to select an area that they want to scan and the drone will fly itself via autopilot. The drone then downloads all of the data and pin points, for example, where the crops are under stress. This allows the problem to be rectified before it has fully developed.

“The first time we used the drones and the software was a neighbouring farmer in Clanwilliam. With the drone, we were able to point out issues that the farm was having, which was caused by a windbreak that was taking away nutrients from the trees. The owner of the farm was blown away,” Paterson says. It was December 2014 and the company was officially born.

Aerobotics’ first client was the University of Stellenbosch’s Plant Readers Laboratory. Eighteen months later, they service several clients and have had over 20 drone sales across the board. Recently the South African Cane Growers’ Association (CANEGROWERS) has signed up too.

Innovations Specialist Richard Howes says, “SA CANEGROWERS, through its commercial arm, Womoba, has formed a partnership with Aerobotics to leverage the advantages of drones for precision agriculture. Current market pressures do not allow the luxury of outdated farming practices.”

He adds that Aerobotics technology will allow sugarcane farmers to reduce costs while increasing yields, improving sustainability and profitability in touch economic times.

In the mining sector, the drones are used to conduct surveys and measure stockpiles. According to a survey of 190 miners by International Data Corporation (IDC), two of every three mining companies globally are looking at remote operations and monitoring centres while half are evaluating new mining methods. A third are looking at robotics and one-fourth at unmanned aerial vehicles – drones.

“Mining is still a relatively new sector for drones, but we are making swift headway in the South African market,” explains Meltzer.

Yet this is just the beginning for the young company. They are looking to move into other large markets including livestock farming and security. They are also continuously developing the science behind their data in conjunction with other experts globally, ensuring that they can give their clients more in-depth analysis and a better understanding of the information that the drones collect.

The American Farm Bureau Federation estimates that farmers could see a return on investment on agricultural drones of $12 (R174) per acre for corn and $2 to $3 (R29 to R44) per acre for soybeans and wheat. With the South African agricultural sector accounting for 3% of the country’s gross domestic product (GDP) and currently facing challenges including increasing resource limitations, depleted soils and over-extracted and polluted water reserves, not to mention a drought, the market is in need of this type of technology.

In fact a recent PwC global report on the commercial applications of drone technology, it is estimated that drones will bring a market value of $32.4 billion to agriculture and $4.3 billion to mining. The report finds that the drone revolution is disrupting industries across the board.

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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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