James Gaston, a speaker at the 2016 PrecisionAg Vision Conference, provides a high-level overview of the conference in a recent HIMSS article where he cites interesting parallels between analytics in agriculture and healthcare. Key takeaways include the topics of Health and Safety, “Rights,” and Syndromic Surveillance. Read on to learn his perspectives about the connections between the agriculture and healthcare sectors in this article by Louise Sulecki, lead systems analyst at the Cleveland Clinic and wife of Meister Media Worldwide Corporate Content Director Jim Sulecki.
Diane Martin, President/CEO of Rhea & Kaiser, attended the PrecisionAg Vision Conference in Phoenix. She recently wrote this article, featuring the event:
Recently I attended the inaugural PrecisionAg Vision Conference with two colleagues from Rhea + Kaiser. It was an industry conference – not a farmer conference – focused on the possibilities and future of precision agriculture throughout the food and fiber value chain. Admittedly, some of the technical discussions were way above my ag tech, IoT, Big Data, agronomic and economic understanding. Still, I have a few insights and observations to share.
What will we call it in the future? Precision ag is earning new monikers such as digital agriculture and data-driven agriculture. I think I heard at least five different labels. Perhaps it’s just semantics, but to me it suggested that the ag industry is embracing Big Data and the Internet of Things, advancing well beyond the practical on-the-farm applications of precision farming.
It’s more than precision farming. The long-term value of precision ag may be upstream rather than on the farm. Integrators like Smithfield use precision ag to ensure feedstuffs for its hog units are grown to its quality and sustainability specifications. Food processors like Campbell’s are tapping into the track-and-trace capabilities of precision ag to validate sustainably sourced claims.
Precision ag is an important risk management tool. Crop insurance companies collect and aggregate the data to inform trigger yield charts and guide claims adjustments. For farmers and retailers, the years of data they’re collecting arms them with compliance data required by regulatory bodies like EPA or NRCS.
Sensing is the next frontier in precision ag. Data from soil-moisture and soil-nutrient sensors to inform irrigation and chemigation are only scratching the surface. We saw a presentation, “The Internet of Tomatoes,” that suggests in-field sensing may help growers consistently produce tomatoes with packers’ desired processing characteristics.
By Julie Parker
President, Tellus Geospatial, LLC (Edmond, OK)
Julie will present as part of a multi-speaker session titled “We Are Not Alone: Lessons Learned From Other Industries” on Thursday, October 20, 9:30 a.m. at the PrecisionAg Vision Conference. For more information on the event, visit PrecisionAgVision.com.
The world’s energy companies have garnered a reputation for being technologically advanced, and certainly, to a significant degree, they are. However, the technological sophistication they possess is not evenly distributed across their enterprises, nor does it permeate all levels (and sizes) of organizations.
It may surprise you to know that many oil field operations are often carried out today with the same rudimentary methods used decades ago. Why? Perhaps the search for an alternative has not been a priority for the end user or their organization. Or maybe options have been implemented, yet fell short of their intended results, and so the old method or technology remains in use.
Regardless of the cause, I would argue that the factors affecting successful widespread technology adoption in my industry also apply to the agriculture industry.
My perspective on the issue of technology adoption stems from a decade of experience creating and deploying geospatial technologies within the energy sector. Through successful and unsuccessful attempts, I have found the geospatial technologies that have been the most widely adopted in my industry and taken up because they met the following conditions:
1) The technology solved a real problem that needed solving.
2) The technology targeted the right audience, whose needs were well-known and understood.
3) The technology was created, tested, and continually refined through real-world experience.
4) The technology fit within the end user’s ecosystem (environment, workflows, equipment, existing technology, etc.)
5) The technology was quickly learned and used by the intended audience.
As I learn more about the agriculture industry, it appears to me that we in the energy business share many of the same challenges relating to technology innovation and adoption.
For example, we struggle with deriving useful, practical knowledge from the inundation of data streaming in from machinery and field sensors, weather, soil, and chemistry data, and real-time feedback from field operations.
And we hear that big data could be the answer. We have various systems providing data and repositories storing it and we spend a lot of time managing and massaging it to get the information we need when and how we need it. And we see that standardizing our data collection methods, platforms, and data could be the answer. We have sales people and technology/industry experts showing us all manner of solutions aimed at making our jobs easier and more efficient and our lands more productive and profitable. And we wonder which of them are merely solutions in search of problems and which of them could be the answer.
Undoubtedly, the road ahead for both our industries will continue to be paved and extended by technological innovation. Our role as providers of food and energy for a growing world will require that we internalize the success factors above and use them as mileposts along the way. In so doing we make the case for “problem-driven” industries within which the promise of technology is realized through a relentless focus on solving the real problems of the intended targets of innovation.
By Rob Dongoski, Global Agribusiness Industry Leader, EY
Dongoski, a speaker at the inaugural PrecisionAg Vision Conference, considers the far-ranging impacts technology is likely to make on global agriculture and food. His presentation will be on “The Agriculture Perspective: Successes and Challenges in Building a Digital Strategy.”
Successful technology is not just about gadgets, data, science advancements, or the infrastructure that enables all of these to function. Success is measured more by how these interact with each other, bring a differentiated experience to the customer/user, and drive value – real or perceived. We have all seen buzz words come and go, but the prospects of the Internet of Things (IoT), analytics, and machine learning appear to be more grounded in evolution than revolution.
While some of these technologies are not entirely new, the ability to produce them at reasonable costs and scale are what may spur meaningful innovation to unlock value in today’s agriculture economy. We have all heard that population growth to nearly 10 billion people will require 70% more food on only 10% more land. While this sounds daunting, we have also seen estimates that we waste 30% of our food and that farmers in emerging markets achieve only 30% of their yield potential. If the application of technology is harnessed appropriately and supported by the right infrastructure and policy, I am confident it can close these gaps.
However, we should also be prepared that increased technology use may introduce new challenges as well. For example, it is conceivable that at some point a consumer in a grocery will routinely be able to use their mobile phone to read the label on the beef in the freezer section and know where the cow was raised, how it was fed, and how it was harvested. While this may satisfy the consumer’s desire to “know their food,” it may also raise challenges related to privacy, supply chain transparency, and bioterrorism. I can certainly envision a day in the very near future where IoT, analytics, and machine learning will create significant value – real and perceived – to the everyday farmer.
Wide-scale technology adoption and impact will need to adapt to the diversity of farming across the world. The 5,000-acre U.S. farmer is certainly different than the subsistence farmer in Ghana. However, just like Africa “leapfrogged” telephony with the mobile phone, will technologies be available in agriculture that allow for a similar leapfrog effect that will transform the subsistent farmer at a rapid rate?
The investment in ag tech is evidence of the impact to be created and the transformation underway in this industry. But, never forget the long-lasting principle – “know thy customer” – if you truly want to make a difference. The promise of ag tech is clear, but the ability to scale and drive adoption and farmer profit ultimately will determine if the potential is realized.
By Jim Sulecki, Corporate Content Director, Meister Media Worldwide
Following is an excerpt from an article in Growing Produce® that speaks to the role of technology in agriculture.
Precision farming and its wider world of “ag tech” is wildly diverse across regions, crop areas, and practical applications in the field. But at its heart is one goal: the so-called “digitization of the farm,” which promises not only to improve the agronomic quantity and quality of the farmer’s output through more data-fueled understanding of what’s going on in the field, but also to make farms more sustainable and with a greater ability to trace products from seed to market, with distinct benefits resonating up and down the food chain.
Read more to learn how the PrecisionAg Vision Conference will bring together some of the brightest agriculture leaders with technology and data experts from across the country to examine the big trends and technologies that will impact the ag industry over the next decade.
By Bill Schmarzo, EMC Global Services
The Internet of Things is creating a “connected” world, where devices are streaming performance and operational data to the world around them. However, just because one is “connected” does not mean one is “smart.” So what is required to transition from “connected” to “smart”? Let’s start with a definition of “smart”:
Creating a “smart” entity is an outcome of optimizing the decisions that support an entity’s business and operational objectives. For example, let’s think about what’s required to create a “smart” city.
What decisions does a city (e.g., city planner, city management, mayor) need to make around citizen quality of life, proactive business development, promoting tourism, top-quality schools and community safety in order to become smart? A “smart” city would look to create (optimized) decisions around the following areas of city operations:
- Bike lanes
- Pedestrian lanes
- Traffic flow
- Road maintenance
- Building permits
- Events management
- Office Parks
Becoming “smart” can provide an over-arching strategy for your data and analytics efforts by creating a vision and a roadmap for where and how organizations can leverage Big Data and the Internet of Things to power their business models. Understanding your organization’s key business initiatives and the supporting decisions is the starting point for that journey.
- You can learn more about how big data fits into crop production agriculture at the PrecisionAg Vision Conference from Bill Schmarzo at his presentation, “The Big Data MBA,” on Tuesday afternoon.
- On Wednesday, Ron Zink, Director, Mobile and Digital Applications at John Deere, will talk about The Internet of Things in his presentation featuring how the IoT is likely to shape agriculture.