Smart Agriculture: AI and the Right Compute Transforming Farming

As the director of public sector and agriculture for the Intel Internet of Things Group, I focus on technologies, ecosystems and partnerships that need technologies that solve problems in a range of areas. We believe the technologies that we focus on: retail, manufacturing, transportation and logistics, and environmental monitoring, align well with the food and agriculture value chain. The investments and uptake in technology adoption in agriculture is somewhere that we can contribute and add value and one of the most promising industries where IoT can bring transformational changes.

At the recent Forbes Live Ag Tech Summit in Salinas, Calif., a gathering of some of the smartest minds from both Silicon Valley and the global agriculture industry resulted in a key takeaway – that most people don’t realize the numerous locations where processing of agriculture and food supply exists. Like farm equipment, where sensors measure everything from water management to nitrogen levels in soil. I not only found this encouraging, but believe that we at Intel are on the right track to supporting the technology evolution in the agricultural industry.

Moo. A dairy cow.

To that end, this past year we’ve been investigating who we can work with, who we can collaborate with and how we can add value in the context of the vision of the Internet of Things (IoT) and agricultural. The potential for transformational change is tremendous.  We believe that IoT can drive greater insight to the physical world, like farming, enabling better decision-making with that greater insight to an interconnected strong and secure ecosystem. We can’t do any of this without partnerships. It’s in our DNA, to build ecosystems and partnerships that drive innovation and really increase the amount of choice in the marketplace.

We recently invested in a company called Filament who has applied blockchain to the agriculture space. Together with Intel, Filament successfully tested tracking fish, a process that begins with attaching IoT-enabled sensors to freshly caught fish, which then continues to track the fish across the supply chain, from monitoring real-time temperature and location all the way to consumers’ plate. We’re still in the early stages, but we believe that blockchain is a viable option and we hope to continue to evaluate it and contribute to this space.

Dell and Intel work to solve honeybee colony collapse.

From individual devices and new analytics opportunities like AI, machine learning, to the cloud, IoT enables sensing and the fusing of information from multiple sources, enabling informed actions for better results. Agriculture uses this entire spectrum, from sensing, analyzing the data and making decisions from the data.

To learn more about smart agriculture, read the Intel IQ article “Farming” or the case study “Keenan and the IoT create a new kind of data farm.” Watch Tony Franklin speaking about smart agriculture on Forbes Live. To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit and Twitter.

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Remote Patient Monitoring: A New Standard of Care for 21st Century Healthcare Delivery

I just came from the quadrennial meeting of the 21st IAGG World Congress of Gerontology and Geriatrics, where I noticed some things worth sharing. There’s been a tectonic shift in industry framing of aging — from costs of infirmity to value of capability and contribution of elders. Not too long ago there was resistance to these notions. Today,  the World Health Organization Strategy on Ageing has codified and recast these and other concepts in a new action plan focused on functional ability that’s  being received with universal acclaim (HuffPost).

What strikes me most is that to achieve this collective vision of healthy & active living at all ages we must also see a tipping point in deployed infrastructure for care beyond the hospital setting. Providers and policymakers must accelerate and expand support for caring for people remotely and in their home. Unless remote care becomes ‘standard of care*’  with medical care, we will never get costs under control and society will forever lack a sufficient remote care digital infrastructure to support independent living into old age.

*Standard of Care: The quality of care that a health care provider should have provided, measured by the level of care that a reasonably skilled health care professional would have provided in similar circumstances. (According to

Enhancing Access

Remote patient monitoring could become a new standard of healthcare.

Don’t get me wrong. Remote and in-home care, especially remote patient monitoring (RPM) is happening, and faster than before.  In recent years, there has been an abundance of evidence demonstrating that RPM, integrated into a care plan, leads to benefits for patients, their families, communities and national health care systems overall. Through RPM, physicians, nurses, elder caregivers and other healthcare providers can gain deeper and more objective insights into patient health, and in many cases, help lead to earlier detection and diagnosis, and therefore earlier and more effective treatment and management of multiple conditions. As one ages, there are also benefits for RPM’s role in helping to maintain “functional ability,” itself essential for a healthier, more active and lower-cost aging process.

In an example of RPM delivering tremendous results, research from the University of Mississippi, Ascension Health and Care Innovations shows that RPM technologies can greatly reduce emergency room visits and hospital readmissions. Such tested RPM applications include videoconferencing with healthcare providers, tablet-based patient education and devices that can prompt and track diet, exercise and medication adherence.

RPM in particular is saving medical costs for systems that use it and improving outcomes for their patients. According to the Veterans Health Administration, RPM can reduce hospitalizations by as much as 40 percent for some diseases, leading to annual savings of $ 6,500 per patient. The estimated annual cost-savings potential of RPM, if adopted widely, could be as high as $ 6 billion.


Transforming Healthcare Policy

Access to that level of care is elusive for most unless you happen to be within one of the few systems that have deployed it. Furthermore, most deployed systems are addressing just one or a few specific conditions. There are of course exceptions in some countries outside the United States (e.g. Singapore ), but largely, comprehensive RPM care is limited and inconsistently available.  Well-defined standards of care could help RPM reach its full potential.

I believe achieving RPM as standard of care is achievable and not in some distant idealized future. The rate of deployments is increasing, the evidence on efficacy and cost savings is overwhelming and irrefutable,  patient and clinician satisfaction when they have deployed is high, and payment systems are changing to recognize and reward  remote care use.

Consider that the average Medicare spending per person doubles between the ages of 70 and 96. Chronic conditions like COPD, heart disease, diabetes, and dementia, which often develop with age, account for nearly 90 percent of U.S. healthcare costs. By connecting patients with physicians and other care providers virtually and enabling quicker ability to address emerging health concerns, RPM can save enormous health costs with respect to reduction of physician and ER visits, early diagnosis of diseases, and mitigation of hospital admissions and readmissions. Over time, investments in the widespread adoption of RPM could help control costs and improve overall care – for governments, healthcare providers and families.

We believe that, to fairly and cost-effectively treat an ever-growing number of people needing care, RPM can and must become a “standard of care” targeting not only post-acute care management for heart attack, stroke and orthopedic and neurological surgeries, but also treatment for chronic conditions like diabetes, COPD, heart disease, and dementia. Our hope is that by 2020, RPM is a medical standard of care and by 2025 at least 50 million people are benefiting annually in the United States from its deployment in medical and independent living use cases.  The technology industry is addressing the technical challenges and the remote care services vendor ecosystem has perfected the care workflows solutions.  Now, all key industry stakeholders must work together to proliferate and democratize access to remote care.  Platforms for RPM, initially deployed for medical uses, can be the digital bedrock of all distributed systems for medical and functional ability support on a national scale.

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Building the Best Autonomous Brain

When I’m bumper-to-bumper in a sea of exhaust fumes and distracted drivers, it seems like autonomous driving can’t get here fast enough. Nor can the potential rewards that come along with fully autonomous vehicles, like far fewer accidents and mobility for people who struggle to get around on their own. To do my part, I’m focusing on how building the best autonomous brain for a car will get us there faster.

5 Things to Know About Autonomous Vehicles

Every day, we’re getting closer to the technology needed to power self-driving cars. But in-vehicle compute needs are complex, and autonomous driving algorithms are changing rapidly. So, the question is: What is the best long-term path to fast, safe decision-making? It all begins with the right compute for the right task. Here are five things you should know about the complex compute for autonomous driving.


It Takes More Than Deep Learning

Artificial intelligence is just one part of the story. And beyond that, AI is more than just deep learning. Yes, deep learning is key in teaching a car how to drive, especially when it comes to computer vision. But there will be several other types of AI at work in the fully autonomous vehicle, from traditional machine learning to memory- and logic-based AI. The fully autonomous vehicle will need a wide range of computing to support three intertwined stages of self-driving: sense, fuse and decide. Each stage requires different types of compute. In the first stage, the vehicle collects data from dozens of sensors to visualize its surroundings. During the second stage, data is correlated and fused to create a model of the environment. Finally, the vehicle must decide how to proceed. System designers need a flexible architecture to support all three stages, with an optimized combination of power efficiency and performance.

With a flexible, scalable architecture of CPUs, Intel Arria 10 FPGAs and other accelerators, our Intel GO automotive solutions portfolio leads the industry with a diverse range of computing elements that support all three stages of driving. But autonomous driving is much more than just in-vehicle compute; that’s why we offer a full car-to-cloud solution including 5G connectivity, data center technologies and software development tools to accelerate autonomous driving.
Smart AI consists of sensing, fusing and deciding.


No Fixed Architecture Can Keep Pace

Before system designers can achieve level four and five driving automation, they must determine how to best use different compute elements within the system to support each type of workload.

No fixed architecture can keep pace with the speed of innovation in AI and system design. Automakers and suppliers will need to be ready to change system designs down the road. Whether it’s to incorporate new algorithms or completely rethink compute to accommodate new workloads, system designers will need a flexible, scalable architecture. Simply put, they need interoperable and even programmable compute elements that don’t require them to start from the ground up every time they want to incorporate a new feature. With a flexible architecture of CPUs, FPGAs and other accelerators, future-ready solutions offer a diverse range of computing elements that can accommodate designs that may change long after hardware and vehicle design decisions have been made.


Driving the Future

Now is a time of tremendous opportunity as we continue to research and respond to the transformational changes before us. From powering Stanford University’s robotic car to serving as a premier board member of the University of Michigan Mobility Transformation Center’s Mcity, Intel is working alongside world-renowned research teams to understand the way people interact with connected cars. Intel has built autonomous vehicle labs in Arizona, California, Germany and Oregon. Here, we’re working hand in hand with our ecosystem partners to optimize customized solutions, road-test autonomous vehicles, and work toward common platforms that will speed broad industry innovation for the promising road ahead.

Learn more about the road to autonomous driving at To stay informed about Intel IoT developments, subscribe to our RSS feed for email notifications of blog updates, or visit and Twitter.

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Industrial Internet Creating Transformational Business Value

This is the second in a two-part blog series on trends in next-generation digital efficiency. In part one, I wrote about how commercial fleet vehicle management systems can drive efficiency while reducing CO2 emissions. To learn more, check out the eBook we created in partnership with GE Ecomagination titled “Digital Efficiency: Driving Decarbonization and Unlocking Business Value Across Industries.”

One of the most pressing global economic challenges today is the global productivity slowdown. That’s why I’m excited to share how the Industrial Internet has made marked advances resulting in both economic and environmental benefits, demonstrating the potential of what is to come as new solutions are developed, deployed and scaled across industries. There’s never been a more promising time for global, industrial digitization solutions.


Improving Digital Efficiency

Numers superimposed on a piece of machinery to represent a smart factory.

For most industrial segments, improving the efficiency of industrial machines by a mere 1 percent used to require a dedicated new technology introduction cycle that can take up to 10 years to develop. Today, thanks to the Industrial Internet, benefits are exceeding far beyond the traditional 1 percent target, without a lengthy technology introduction cycle or replacing hardware.

The industrial sector accounts for the largest share of energy consumption delivered and accounts for more than half of total delivered energy. This is why the Industrial Internet is transformative and opens the door to accelerated resource productivity and reduced environmental impact across global industrial systems such as power generation, oil and gas, aviation and rail transportation.


Renewable Energy: GE’s Brilliant Wind Farm

People in T-shirts and hardhats check out a laptop while wind turbines twirl across the landscape.

One of my favorite examples of the transformational change capable with the Industrial Internet is seen in the way GE’s PowerUp Platform has been extended to enable GE Digital Wind Farm. With this solution, GE extends analytics and optimization beyond a single wind turbine to the entire wind farm. GE harnessed the power of the emerging Industrial Internet to create the Digital Wind Farm, a dynamic connected and adaptable wind energy platform that pairs wind turbines in a wind farm with digital infrastructure to optimize efficiency across the entire wind farm. The GE Digital Wind Farm solution generates up to 20 percent more energy output thanks to the GE Predix-ready gateway with Intel technology.

This platform can account for the wind farm’s topology, surrounding geography, wake effects, and other inputs to control individual wind turbines and optimize the operation as a whole. Through these techniques, the Digital Wind Farm technology boosts a wind farm’s energy production by up to 20 percent and could help generate up to an estimated $ 50 billion value for the wind industry. The Digital Wind Farm uses interconnected digital technology to address a long-standing need for greater flexibility in renewable power.


The Future Looks Bright

A woman examines rows of light-emitting diodes (LEDs).

As seen with GE’s Digital Wind Farm solution, Intel processors underline GE’s Predix solutions and provide both high power and flexibility. Powerful processors embedded in machines allow for software developed on Predix to run at the most effective point, embedded either in operations or in the cloud. Scaling out other solutions across industries in this manner, the combination of GE software and Intel hardware will provide the foundation for digital efficiency by enabling the development of Industrial Internet applications that provide the full range of potential economic and environmental benefits.

To be sure, a new world of possibilities is being unlocked through the Industrial Internet and digital solutions currently available and under development are just the tip of the iceberg. At GE and Intel, we are excited about the opportunity to play a role in helping to confront global resource challenges and accelerate the pathway to the low-carbon economy using digital technologies. The future has just begun and the best is yet to come.

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Commercial Fleet Vehicle Management System Drives Efficiency, CO2 Reductions

This is the first in a two-part blog series on trends in next-generation digital efficiency. To learn more, check out the eBook we created in partnership with GE Ecoimagination titled, “Digital Efficiency: Driving Decarbonization and Unlocking Business Value Across Industries.”

Looking out across the vast Internet of Things (IoT) landscape, we’re seeing the emergence of digital technologies ushering in a new era of productivity for business and industrial operations, while also enabling new tools to approach global environmental challenges. Digital solutions, enabled by the Industrial Internet, can now lower operation costs, increase output, use natural resources more efficiently, and lower environmental impact enabling tremendous digital efficiency. The transformational opportunities made possible with digital efficiency as a critical differentiator are enormous.

Let’s look at fleet efficiency, for example. In a scenario where just a handful of digital solutions are scaled across key industries, such as fleet management, we estimate a potential return of $ 81 billion in annual cost savings to businesses, paired with a reduction of 823 metric tons of carbon dioxide emissions per year. Let’s take a closer look at one such solution for improved cost-saving and energy efficiency.


Driving Fleet Efficiency

Truck wheels roll on, across an endless desert, sensing the future.

The big wheels of innovation were turning with a fleet management proof of concept enabled by Intel processors and GE’s Predix solutions for high power and flexibility. In this example, Intel assembled and tested a fleet management system proof of concept that can be customized to easily fit into a wide variety of commercial vehicles including taxis, school buses, and logistic freight vehicles. The architecture features an in-vehicle system based on the Intel Atom processor E3827 and sports data management, telematics, smart surveillance, and mobile applications.

Rather than fleet operators maintaining data manually, this solution collects real-time telematics data from sensors located inside the vehicle and sends it over as an Internet connection to the cloud, where it can be distributed to stakeholders or further processed by the data analytics software. The system gathers data associated with vehicles, terminals, stops, users, and driver schedules, allowing operations to run more efficiently and creating optimized routes.

Additionally, this proof of concept gathers driving pattern data. The occurrences of aggressive acceleration, braking, and turning were reduced by 57 percent, 30 percent, and 17 percent. As a result of the study, the drivers reduced their speed, which improved fuel economy. The application of data-driven insights also helped improve routes and driving behavior, as well as reduce fuel consumption and greenhouse gas emissions.


Digital Decarbonization

Sensors awaken, a bright car-to-cloud future, autonomous now.

As we’ve seen, the potential benefits of digital fleet management technologies, enabled by the Industrial Internet, to provide global environmental benefits will be dramatic and provide large market opportunities. Our analysis indicates that by 2030, the global gap between individual country carbon dioxide targets and carbon dioxide emissions is expected to grow to 2.6 Gt CO2 per year by 2030. This means that digital solutions alone have the potential to close nearly one-third of the gap between expected carbon dioxide emissions and stated country commitments!

This is a truly exciting time and the digital efficiency journey has just begun. The time is now for businesses around the world to lead their own digital efficiency revolution to increase their competitiveness and better manage the environmental impact of their operations.

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