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 . 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 . 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.
 The UN Department of Economic and Social Affairs, “World Population Prospects: The 2017 Revision”
 Business Insider Intelligence, 2016 report: https://www.businessinsider.com/internet-of-things-smart-agriculture-2016-10
ME and Africa Consumer tech spending to hit $149bn
Reaching $130bn this year, consumer spending on technology in the Middle East and Africa is expected to grow just 4% a year.
Consumer spending on technology in the Middle East and Africa (MEA) is forecast to total $130.8 billion this year, a year-on-year increase of 4.1%. According to the latest Worldwide Semiannual Connected Consumer Spending Guide from International Data Corporation (IDC), consumer purchases of traditional and emerging technologies will remain strong over the 2019–2023 forecast period, increasing at a five-year compound annual growth rate (CAGR) of 3.5% to reach $149.4 billion in 2023.
86.3% of all consumer technology spending in 2019 will be on traditional technologies such as mobile phones, personal computing devices, and mobile telecom services. Mobile telecom services (voice and data) will account for 68.7% of this amount, followed by mobile phones which will account for 26.6%. Spending growth for traditional technologies will be relatively slow, with a CAGR of 2.4% for the 2019–2023 forecast period.
“Faster connectivity, combined with declining data service costs from telecom service providers and the need for end users to use telecom services for an increasing number of devices, will ensure that consumer spending on traditional technologies will continue to grow,” says Fouad Charakla, IDC’s senior research manager for client devices in the Middle East, Turkey, and Africa.
Emerging technologies, including AR/VR headsets, drones, on-demand services, robotic systems, smart home devices, and wearables, will deliver strong growth with a five-year CAGR of 10.2%. This growth will see emerging technologies account for 17.1% of overall consumer spending in 2023, up from 13.7% in 2019. Smart home devices and on-demand services will account for around 93% of consumer spending on emerging technologies by the end of the forecast period.
“The low penetration of smart home devices in the region, combined with growing efforts from market players to educate home users on the benefits and usage of these devices, will serve as an engine of growth for consumer spending on emerging technologies,” says Charakla. “A large portion of end users are already looking to invest in devices that will improve their productivity and quality of life, two key demands that smart home devices can be positioned to fulfil.”
On-demand services represent a new addition to IDC’s Worldwide Semiannual Connected Consumer Spending Guide. “On-demand services enable access to networks, marketplaces, content, and other resources in the form of subscription-based services and includes platforms such as Netflix, Hulu, and Spotify, among others,” says Charakla. “As connected consumers juggle multiple services across their devices, it is essential for technology providers to understand how the adoption of these various technologies and services will impact their customers’ experiences in the future.”
Communication and entertainment will be the two largest use case categories for consumer technology, representing more than 79% of all spending throughout the forecast. More than 70% of all communication spending will go toward traditional voice and messaging services in 2019. Entertainment spending will be dominated by watching or downloading TV, videos and movies, as well as listening to music and downloading and playing online games. The use cases that will see the fastest spending growth over the forecast period are augmented reality games (49.5% CAGR).
The Worldwide Semiannual Connected Consumer Spending Guide quantifies consumer spending for 22 technologies in ten categories across nine geographic regions. The guide also provides spending details for 23 consumer use cases. Unlike any other research in the industry, the Connected Consumer Spending Guide was designed to help business and IT decision makers to better understand the scope and direction of consumer investments in technology over the next five years.
Could robots replace human tennis players?
While steeped in tradition, tennis has embraced technology on multiple fronts: coaching, umpiring and fan experiences. Since the early 2000s, the Sony-owned Hawk-Eye system has been assisting tennis umpires in making close calls. At Wimbledon, IBM’s Watson AI analyses fan and player reactions in real-time video footage from matches to create highlight reels just minutes after the end of a match.
Meanwhile, at the ATP Finals in London, similar data analysis is being carried out by digital services and consulting firm Infosys.
GlobalData’s Verdict deputy editor Rob Scammell hears the future of tennis discussed at a recent panel discussion about the use of data analytics and technology in the game.
Scammel writes: “Infosys has been partnered with ATP for five years, providing features such as its cloud-based platform, which leverages artificial intelligence to analyse millions of data points to gain insights into the game.
“Players and coaches can also make use of the Infosys’ Players and Coaches Portal, allowing them to “slice and dice” matches on an iPad with 1,000 data analytics combinations. This is data crunching is vital according to Craig O’Shannessy, strategy analyst for the ATP World Tour and a coach for 20 years – including for the likes of Novak Djokovic.
O’Shannessy says: “Video and data analytics is crucial for giving players an edge. It’s about finding out of 100 points, the 10 or 15 that matter the most, and explaining that these are the patterns of play that you want to repeat in these upcoming games to win those matches.”
However, although Chris Brauer, director of innovation at the Institute of Management Studies at Goldsmiths, University of London, asked whether the “inevitable conclusion” of technological innovations in tennis was removing humans from the game entirely. ATP chair umpire and manager Ali Nili suggested that while there could one day be robot players adjudicated by robot umpires, it would be an entirely different sport.
Nili told GlobalData: “At ATP, we’re most proud of our athletes. It’s our athletes which make the tennis exciting. It’s how fast they are, how strong they are being. As humanbeings, we compare them to us and we’re fascinated by the things that they’re able to do. They’re the number one attraction for anyone who comes in, watches tennis, and everything else is secondary, you know, all the data and everything else, because we try to make our athletes more appealing.”
Could robots replace human tennis players?
Raghavan Subramanian, associate vice president and head of Infosys Tennis Platform, says it’s a “very philosophical question” and that we can look to the precedent set by other ‘man vs machine’ face-offs.
“In chess, we had [Garry] Kasparov play against the computer. So I think the natural first transition will not be two robots playing against each other, but one robot, possibly playing against the best player today. That’s the first possible bridge before two robots play.”