Food & Agriculture Quarterly March 2018 | Page 5

MARCH 2018 FOOD & AGRICULTURE QUARTERLY PAGE 5 food production . If we are going to bridge what now seems like an insurmountable gap between projected demand and expected supply , the agricultural industry is going to have to increase its efficiency and output . This will be no small feat , as many of the crops currently grown are facing obstacles to continued growth , either by environmental threats that create inhospitable farming environments as a result of climate change , or by forming immunities to many current pesticide regimes that are meant to protect the crops from disease and weeds .
Luckily , there are at least four major areas in which the IoT promises to help the agricultural industry tackle these unique hurdles . The first three areas focus on production-side data collection and analysis . First , analytic data can be harnessed for use in Precision Agriculture . Second , IoT and Big Data can be used in livestock and fishery management to monitor the health of a variety of livestock , and be proactive in health and disease management . Third , agricultural equipment can be monitored and tracked for systems of irrigation , tractor routes , and for collection of data from autonomous agri-vehicles , precision planting , crop spraying and harvesting . This data collection can also be helpful for fault management and proactive maintenance .
These technologies collect data by remotely observing , measuring , and monitoring crops and environmental conditions in real time , and saving that data for later comparison to assess how the next growing season compares to the last . One example is a technology product that combines data derived from soil humidity and weather data sensors placed in the field , which in turn uses predictive analysis for when the farmer needs to irrigate , in which part of the field and for how long .
Other technologies focus on monitoring pests , using a system of censored traps and photography to count , in real time , the number of pests in given parts of the field . Some utilize a combination of various photography methods ( including drone photography ) to estimate yield production via image analysis .
The fourth major area in which the IoT and Big Data promise to help the agricultural industry tackle its unique hurdles is through the collection and analysis of supply chain and logistics data . The IoT is especially important in this context , as it allows all of the major stakeholders in the agricultural industry to not only collect data , but share and use that data across different parts of the industry . The major stakeholders represent the steps it takes for food to get from the farm to the consumer : the farmer , the shipping and travel logistics teams , the distribution centers and finally the retailers . When supply and demand data , for example , can be gathered by the retailers and distributors , and then shared with the farmers and logistics teams , food waste can be avoided by appropriately harvesting and sending product where it is most likely to be sold to consumers .
All this said , there are significant challenges to fully realizing the benefits the IoT and Big Data promise for the agricultural industry . For one , sharing of data and the results of predictive analytics can raise significant antitrust concerns . Additionally , as with all data technologies , there are definite confidentiality concerns , both as to ownership and control of the collected data and analysis . There are also financial complexities ,
© 2018 Porter Wright Morris & Arthur LLP