As the backbone of developing economies, agriculture not only serves to feed a nation but creates employment and, often, contributes significantly to the GDP. According to the Food and Agriculture Organisation of the United Nations (FAO), feeding a world population of 9.1 billion people in 2050 will require a 70% increase in overall food production, highlighting the need for increased, and more efficient, agricultural activities globally. Additionally, the FAO states that 80% of farmland in Asia and sub-Saharan Africa is managed by smallholders working on 10 hectares or less.
According to Thomas Fuerst, WING Marketing at Nokia, while research clearly shows that technology can add tremendous value to South African farmers, the uptake has not been what it should be, particularly among subsistence and small-scale farmers. “This is likely due to the perceived costs associated with technology,” he says.
The adoption of technology in agriculture also requires that various stakeholders work together. In a report done by the University of Stellenbosch for the Western Cape Department of Agriculture, while agricultural technology will result in higher yields, reduced costs and improved nutritional value of foods, it needs the farming sector, government and education institutions to work together. “Crop disease, pests, and drought are some of the biggest issues facing agriculture in sub-Saharan Africa,” says Fuerst. According to CAB International crop pests and disease account for close to half of the total crop losses in developing countries and in a 2017 UN report, it was stated that about 200 000 people, mostly from developing countries, die every year from pesticide poisoning. “By using technology, and more particularly the Internet of Things (IoT), we can arm farmers with more detailed data about their farm as well as the macro environment to assist them in planning their crops more accurately and thereby driving a better yield, while eliminating risk,” he says.
Fuerst says there are three key challenges that need to be solved, the first of which is data availability and integrity. “The farmer has a small plot and can’t necessarily afford to buy different types of sensors to measure moisture, temperature or pests and put them on their small farm. Even if they could afford it, they need to know about weather and other conditions from a macro or wide area perspective, so that can predict what the impact of these will be on them in the future.”
The second challenge is what do they do with the data. They need tools that help them know what the weather is, what pests are coming, etc. and enable them to make decisions based on that information. The third challenge is the business model – it must be affordable for both the operator and the smaller farmers for it to be successful.
“If you look at developing economies, you don’t always have the large commercial farms that you find in developed countries. You have lots of smaller farmers who are working a small plot of land and operate in almost subsistence mode. That means that they have a limited budget available to spend on rolling out technology solutions, even if those will make their farms run more efficiently and save them costs. They require a solution that is packaged as an affordable ‘as-a-service’ package that will enable them to gather data to drive more intelligent decisions. This is where IoT comes into play,” he says.
Nokia’s Smart Agriculture-as-a-service solution runs on the Nokia Worldwide IoT Network Grid (WING), which is a global horizontal platform which allows telcos to notonly roll out IoT services more quickly on their network but gives them the flexibility to scale globally when they need to. “They don’t have to rely on the cost and complexity of things like roaming agreements that you have with traditional mobile phone services. It allows operators to roll out IoT services much quicker and scale their network much faster without investing huge amounts of CAPEX,” says Fuerst.
Nokia works with the operator to roll out sensors that detect moisture, temperature, wind speed, and pests and deploy them across their whole network, not just in one province or town. “This way they are gathering data about the weather, pests and climate conditions across a far wider area and provide this data to the farmersas a service. There’s a smartphone, tablet or a computer application where they can access and leverage that data. It gives them access to data on weather conditions, pest trends, etc. and they can make smarter decisions about irrigation, applying pesticides, when to harvest or not and things like that. The farmer then also has the ability, if there’s some specific problem they have, they can send an SMS to an advisory centre and get advice on how to solve a specific problem.”
The operator, on the other hand, doesn’t have to invest a lot of CAPEX to roll out this IoT network and then put all these sensors on it – they can leverage WING to keep their costs low for the infrastructure and all they have to do is buy these sensors and put them across their network. Then they can access all that data and it can allow them, with minimal CAPEX, to now offering a service to their farmers at a low enough price so that the business model works for both parties.
Addressing the issue of future food requirements resides not in trying to find and develop new agricultural lands but in transforming current farms into more ’intelligent’ ones for sustainable agriculture. “A successful smart agriculture program can be achieved through collaboration between the various stakeholders – technology providers, device manufacturers, platform providers, governmental entities, non-governmental organizations, agricultural cooperatives, agricultural companies, and farmers,” Fuerst concludes. “Critical to this, however, is finding the right business model, which works for both the farmer and the network operator. The WING smart agriculture as-a-Service is unique in this regard because it allows farmers to benefit from IoT technology without the need to invest in it while giving the operator a pay-as-you-go business model that limits investment demands while offering a clear path to new revenues.”
Why your first self-driving car ride will be in a robotaxi
Autonomous driving will take longer than we expect, and involve less ownership than the industry would like, writes Intel’s AMNON SHASHUA
As we all watch automakers and autonomous tech companies team up in various alliances, it’s natural to wonder about their significance and what the future will bring. Are we realizing that autonomous driving technology and its acceptance by society could take longer than expected? Is the cost of investing in such technology proving more than any single organization can sustain? Are these alliances driven by a need for regulation that will be accepted by governments and the public or for developing standards on which manufacturers can agree?
The answers are likely a bit of each, which makes it a timely opportunity to review the big picture and share our view of where Intel and Mobileye stand in this landscape.
Three Aspects to Auto-Tech-AI
There are three aspects to automotive-technology-artificial intelligence (auto-tech-AI) that are unfolding:
- Advanced driver-assistance systems (ADAS)
- Robotaxi ride-hailing as the future of mobility-as-a-service (MaaS)
- Series-production passenger car autonomy
With ADAS technologies, the driver remains in control while the system intervenes when necessary to prevent accidents. This is especially important as distracted driving grows unabated. Known as Levels 0-2 as defined by the Society of Automotive Engineers (SAE), ADAS promises to reduce the probability of an accident to infinitesimal levels. This critical phase of auto-tech-AI is well underway, with today’s penetration around 22%, a number expected to climb sharply to 75% by 2025.1
Meanwhile, the autonomous driving aspect of auto-tech-AI is coming in two phases: robotaxi MaaS and series-production passenger car autonomy. What has changed in the mindset of many companies, including much of the auto industry, is the realization that those two phases cannot proceed in parallel.
Series-production passenger car autonomy (SAE Levels 4-5) must wait until the robotaxi industry deploys and matures. This is due to three factors: cost, regulation and geographic scale. Getting all factors optimized simultaneously has proven too difficult to achieve in a single leap, and it is why many in the industry are contemplating the best path to achieve volume production. Many industry leaders are realizing it is possible to stagger the challenges if the deployment of fully autonomous vehicles (AVs) aims first at the robotaxi opportunity.
Cost: The cost of a self-driving system (SDS) with its cameras, radars, lidars and high-performance computing is in the tens of thousands of dollars and will remain so for the foreseeable future. This cost level is acceptable for a driverless ride-hailing service, but is simply too expensive for series-production passenger cars. The cost of SDS should be no more than a few thousand dollars – an order of magnitude lower than today’s costs – before such capability can find its way to series-production passenger cars.
Regulation: Regulation is an area that receives too little attention. Companies deep in the making of SDSs know that it is the stickiest issue. Beside the fact that laws for granting a license to drive are geared toward human drivers, there is the serious issue of how to balance safety and usefulness in a manner that is acceptable to society.
It will be easier to develop laws and regulations governing a fleet of robotaxis than for privately-owned vehicles. A fleet operator will receive a limited license per use case and per geographic region and will be subject to extensive reporting and back-office remote operation. In contrast, licensing such cars to private citizens will require a complete overhaul of the complex laws and regulations that currently govern vehicles and drivers.
The auto industry is gradually realising that autonomy must wait until regulation and technology reach equilibrium, and the best place to get this done is through the robotaxi phase.
Scale: The third factor, geographic scale, is mostly a challenge of creating high-definition maps with great detail and accuracy, and of keeping those maps continuously updated. The geographic scale is crucial for series-production driverless cars because they must necessarily operate “everywhere” to fulfil the promise of the self-driving revolution. Robotaxis can be confined to geofenced areas, which makes it possible to postpone the issue of scale until the maturity of the robotaxi industry.
When the factors of cost, regulation and scale are taken together, it is understandable why series-production passenger cars will not become possible until after the robotaxi phase.
As is increasingly apparent, the auto industry is gravitating towards greater emphasis on their Level 2 offerings. Enhanced ADAS – with drivers still in charge of the vehicle at all times – helps achieve many of the expected safety benefits of AVs without bumping into the regulatory, cost and scale challenges.
At the same time, automakers are solving for the regulatory, cost and scale challenges by embracing the emerging robotaxi MaaS industry. Once MaaS via robotaxi achieves traction and maturity, automakers will be ready for the next (and most transformative) phase of passenger car autonomy.
The Strategy for Autonomy
With all of this in mind, Intel and Mobileye are focused on the most efficient path to reach passenger car autonomy. It requires long-term planning, and for those who can sustain the large investments ahead, the rewards will be great. Our path forward relies on four focus areas:
- Continue at the forefront of ADAS development. Beyond the fact that ADAS is the core of life-saving technology, it allows us to validate the technological building blocks of autonomous vehicles via tens of new production programs a year with automakers that submit our technology to the most stringent safety testing. Our ADAS programs – more than 34 million vehicles on roads today – provide the financial “fuel” to sustain autonomous development activity for the long run.
- Design an SDS with a backbone of a camera-centric configuration. Building a robust system that can drive solely based on cameras allows us to pinpoint the critical safety segments for which we truly need redundancy from radars and lidars. This effort to avoid unnecessary over-engineering or “sensor overload” is key to keeping the cost low.
- Build on our Road Experience Management (REM)™ crowdsourced automatic high-definition map-making to address the scale issue. Through existing contracts with automakers, we at Mobileye expect to have more than 25 million cars sending road data by 2022.
- Tackle the regulatory issue through our Responsibility-Sensitive Safety (RSS) formal model of safe driving, which balances the usefulness and agility of the robotic driver with a safety model that complies with societal norms of careful driving.
At Intel and Mobileye, we are all-in on the global robotaxi opportunity. We are developing technology for the entire robotaxi experience – from hailing the ride on your phone, through powering the vehicle and monitoring the fleet. Our hands-on approach with as much of the process as possible enables us to maximize learnings from the robotaxi phase and be ready with the right solutions for automakers when the time is right for series-production passenger cars.
On the way, we will help our partners deliver on the life-saving safety revolution of ADAS. We are convinced this will be a powerful and historic example of the greatest value being realized on the journey.
Professor Amnon Shashua is senior vice president at Intel Corporation and president and chief executive officer of Mobileye, an Intel company.
Sea of Solitude represents mental health issues through gaming
It’s a game that provides a tasteful visual representation of mental health issues. BRYAN TURNER dives into the Sea of Solitude.
Disclaimer: This review is based on four hours of gameplay.
Sea of Solitude, the latest adventure game by Jo-Mei Games and EA Games, takes a sobering look at loneliness. It represents this loneliness visually, using light and dark environmental changes, as well as creatures players must encounter. The main character, Kay, must make it through the sea without finding herself trapped in a sea of loneliness. She meets fantastical creatures along her journey, and she must help them solve their challenges while keeping herself in a sane environment.
The game is systematic in the way it represents its important aspects. It starts with a striking visual art style and a soft storyline, which gives characters a chance to absorb the beauty of the game. As one gets a hang of the controls and used to the art style, the story kicks it up a few notches to reveal the harrowing backstories of the creatures that reside in the sea Kay must travel.
In particular, it features a creature that keeps flying away from Kay. This was frustrating because the previous chapter of the game presents a backstory for the creature that was not only devastating to the main character, but also to the player. Once Kay meets this creature, players must be ready to cry. It’s a brilliantly crafted story and hats off to Jo-Mei Games for being great storytellers.
Cornelia Geppert, CEO of Jo-Mei Games, told EA: “Sea of Solitude centres on the essence of loneliness and tugs on the heartstrings of its players by mirroring their own reality. It’s by far the most artistic and personal project I’ve ever created, written during a very emotional time in my life. Designing characters based on emotions was a deeply personal achievement for our team and we’re so excited for players to soon experience Kay’s powerful story of self-discovery and healing.”
Generally, I steer clear of games that are metaphors about mental health issues because they tend to be crass in how they address mental health. Sea of Solitude is quite different because of its level of relatability. Other games about mental health tend to be about a specific disorder that not many people experience, while loneliness is something that so many of us experience. Additionally, the representation of how loneliness affects Kay in the real world is sharp but tasteful. The combination of relatability and respectful representation is what makes the game’s story so brilliant.
Another great aspect of this game is the music scoring. It uses sound and the absence of sound very carefully to invoke the right feelings expected from players. The game wouldn’t be as good with the sound off and subtitles on, so future players are recommended to turn up the volume or put on headphones.
The game is long for an indie game, at around three or four hours of gameplay until the end is reached. Several sources say there is a hidden ending, so players can look out for that in a second playthrough.
The game’s story isn’t perfect, though. The eventual sameness of creature encounters is a little disappointing. This may be down to the expectation of being extremely devastated by all the stories of the creatures, especially when one is less than devastated by the subsequent stories. One of the most affecting creature stories was also presented at the beginning of the game, which set the bar very high for the rest of the creatures.
One creature, in particular, tries very hard to have the greatest emotional impact, but this comes across as blunt and dampens the meaning of what it was supposed to represent.
While I didn’t mind sharp representation, the perception of themes like bullying, estrangement, and suicidal thoughts may vary in appropriateness from player to player. Prospective players with existing painful mental health issues should consult gameplay videos, like the one below, before purchasing the game, to gauge appropriateness.
Overall, the game is incredible at connecting with what it is to be human and what it means to be lonely. Dealing with issues as physical creatures is a great touch, as the main character tends to resolve the problems of the creature by understanding what the problems mean.