Algorithm could streamline harvesting of hand-picked cropsMarch 13, 2018
Farmers are the latest beneficiaries in a world of data analytics. Over the past few years, precision agriculture has been helping farmers make smarter decisions and producing a bigger yield. But most of the studies to date have been in row crops harvested by large machines, made possible by data collected by drones and other means. However, Richard Sowers, a professor of industrial and enterprise systems engineering and mathematics at the University of Illinois at Urbana-Champaign, and a team of students have developed an algorithm that promises to give valuable information to farmers of crops picked by hand.
Sowers, along with students Nitin Srivastava and Peter Maneykowski have developed an algorithm which will help streamline the workforce of highly perishable hand-picked crops. Their paper, Algorithmic Geolocation of Harvest in Hand-Picked Agriculture, which will appear in Natural Resource Modeling, presents the results of a study conducted at the harvest of strawberry patches at Crisalida Farms in Oxnard, Calif. Less than a year ago, Sowers co-authored a paper titled, Hand-picked specialty crops 'ripe' for precision agriculture techniques, addressing the timing and transport of such crops.
"The strawberries that you put on your ice cream or cereal are for the moment picked by a crew of 10 or so workers, who mostly earn a wage per box collected," Sowers noted. "For the consumer, it important that the strawberries are of good quality and look nice."
According to Sowers, the strawberries that appear in clam shells that you find at the market or at your local grocery store are largely in the same condition as they were when they were picked from the field. They are loaded in a box, then a bigger box, then on a pallet and finally onto a truck. The process is then reversed at the market.
"One of the aspects that I'm interested in is the fact that there are humans involved in picking," Sowers said. "Just like Internet browsing history differs from person to person, along similar lines, a workers' ability to harvest strawberries is different. This brings up the question: how do you think about data in that industry? Because the human variability has a huge effect.
"Figuring out what is going on in the field is an important question," he added. "Identifying that certain parts of the field are producing a higher or lower quality harvest can be valuable in harvest strategy."
Rather than requiring a worker to enter data during harvest, which would slow down the process, Sowers' team was able to pinpoint exact movement of each worker through GPS tracking on a smart phone each carried with them. Based on that data, the team developed an algorithm to predict the amount of completed boxes.
The data promises to ultimately lead to more precision techniques for harvesting. For instance, one set of quality control typically occurs at the edge of field and oftentimes there is a backlog of workers waiting in the que. More data will better help plan for best times to provide this control as well as schedule forklifts to pick up pallets and put them in a cooler. Time is of the essence as hot weather can have a dramatic effect to the quality of the produce.
"At the moment, we're just trying to track," Sowers noted. "You can't manage what you can't measure. We're trying to measure what is going on in the field actually in the field, not at the edge of the field where data is currently being collected. If you know moment by moment how much is being harvested, you can better schedule, rearrange harvest crews or re-task."
Sowers further iterates the importance of this measurement to the industry because miscalculation of the workforce could completely eliminate profit.
"If that happens, all the nutrients that went into it (water, fertilizers, nitrogen, etc.) is just wasted," he said. "If you can better allocate resources and prevent or lessen the time that some of those stacks of berries are sitting in the field, that's a win."
The team successfully proved that these behaviors can be tracked and analyzed and is planning to return to California to refine it.
"There is a more and more appreciation for data in this industry," Sowers said. "I'd like to go back and do this on a larger scale so that we can try to compare this to something which is at a production grade. In order to actually have an impact, we need to understand and process the data at a level of certainty which is as good as or comparable to what is needed to actually make some decisions for re-allocating people and for optimizing the layout of fields."
University of Illinois College of Engineering
Related Algorithm Articles:
A new algorithm helps scientists record the activity of individual neurons within a volume of brain tissue.
A new algorithm generates practical paper-folding patterns to produce any 3-D structure.
Scientists at Princeton University have developed a new algorithm to track neurons in the brain of the worm Caenorhabditis elegans while it crawls.
Community detection is an important tool for scientists studying networks, but a new paper published in Science Advances calls into question the common practice of using metadata for ground truth validation.
Humans, like virtually all other complex organisms on Earth, have adapted to their planet's 24-hour cycle of sunlight and darkness.
Researchers from the Tokyo-based company Silicon Studio, led by Spanish data scientist África Periáñez, have developed a new algorithm that predicts when a user will leave a mobile game.
Scientists from Russia and Singapore created an algorithm that predicts user marital status with 86% precision using data from three social networks instead of one.
Much attention has been paid to the Taylor series expansion (TSE) method these years, which has been extensively used for solving nonlinear equations for its good robustness and accuracy of positioning.
The article that received the best student-paper award in the Tenth International Conference on Web Search and Data Mining (WSDM 2017) builds algorithmic techniques to mitigate the rising polarization by connecting people with opposing views -- and evaluates them on Twitter.
In hopes of creating better access to medical care, Stanford researchers have trained an algorithm to diagnose skin cancer.
Related Algorithm Reading:
Introduction to Algorithms, 3rd Edition (MIT Press)
by Thomas H. Cormen (Author), Charles E. Leiserson (Author), Ronald L. Rivest (Author), Clifford Stein (Author)
A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-based flow.
Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The... View Details
Algorithms (4th Edition)
by Robert Sedgewick (Author), Kevin Wayne (Author)
This fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms is the leading textbook on algorithms today and is widely used in colleges and universities worldwide. This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing--including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the... View Details
Algorithms to Live By: The Computer Science of Human Decisions
by Brian Christian (Author), Tom Griffiths (Author)
What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of the new and familiar is the most fulfilling? These may seem like uniquely human quandaries, but they are not. Computers, like us, confront limited space and time, so computer scientists have been grappling with similar problems for decades. And the solutions they’ve found have much to teach us.
In a dazzlingly interdisciplinary work, Brian Christian and Tom Griffiths show how algorithms developed for computers also untangle very human questions. They explain how to have... View Details
Grokking Algorithms: An illustrated guide for programmers and other curious people
by Aditya Bhargava (Author)
Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.
Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun,... View Details
by Sanjoy Dasgupta Algorithms (Author), Christos H. Papadimitriou Algorithms (Author), Umesh Vazirani Algorithms (Author)
This text, extensively class-tested over a decade at UC Berkeley and UC San Diego, explains the fundamentals of algorithms in a story line that makes the material enjoyable and easy to digest. Emphasis is placed on understanding the crisp mathematical idea behind each algorithm, in a manner that is intuitive and rigorous without being unduly formal.
Features include: The use of boxes to strengthen the narrative: pieces that provide historical context, descriptions of how the algorithms are used in practice, and excursions for the mathematically sophisticated.
This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students.The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The... View Details
The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World
by Pedro Domingos (Author)
"Wonderfully erudite, humorous, and easy to read." --KDNuggets
In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner-the Master Algorithm-and discusses what it will mean for business, science, and society. If... View Details
Once Upon an Algorithm: How Stories Explain Computing (MIT Press)
by Martin Erwig (Author)
How Hansel and Gretel, Sherlock Holmes, the movie Groundhog Day, Harry Potter, and other familiar stories illustrate the concepts of computing.
Picture a computer scientist, staring at a screen and clicking away frantically on a keyboard, hacking into a system, or perhaps developing an app. Now delete that picture. In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem... View Details
Data Structures and Algorithms in Java (2nd Edition)
by Robert Lafore (Author)
Data Structures and Algorithms in Java, Second Edition is designed to be easy to read and understand although the topic itself is complicated. Algorithms are the procedures that software programs use to manipulate data structures. Besides clear and simple example programs, the author includes a workshop as a small demonstration program executable on a Web browser. The programs demonstrate in graphical form what data structures look like and how they operate. In the second edition, the program is rewritten to improve operation and clarify the algorithms, the... View Details
Algorithms of Oppression: How Search Engines Reinforce Racism
by Safiya Umoja Noble (Author)
A revealing look at how negative biases against women of color are embedded in search engine results and algorithms Run a Google search for “black girls”—what will you find? “Big Booty” and other sexually explicit terms are likely to come up as top search terms. But, if you type in “white girls,” the results are radically different. The suggested porn sites and un-moderated discussions about “why black women are so sassy” or “why black women are so angry” presents a disturbing portrait of black womanhood in modern society. In Algorithms of... View Details