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Introduction
Internet of things (IoT) technology and big data applications are poised to play a key role in ramping up global food production to feed billions in the coming decades. Experts are envisioning a data-driven future, wherein IoT-based technology ranging from sensors on farm equipment, self-driving tractors, drones and GPS imaging to weather tracking would not only enable farmers to feed the world but also cope better with the limited supply of fossil fuel, water and arable land (Ray, 2017; Lohr, 2015). Reports suggest that the number of connected agricultural devices are growing from 13 million in 2014 to 225 million in 2024 and the installation of IoT devices is rising at a compounded annual growth rate of 20 per cent worldwide (Machina Research, 2016; Meola, 2016). Accounts from the popular press allude to the advent of “agriculture 3.0,” which entails exploiting data from many sources, such as sensors on farm equipment and plants, satellite images and weather tracking (Lohr, 2015). Following the advent of big data analytics in agriculture, large volumes of data, which could not be quantifiable in the past, can now be analyzed through statistical models and algorithms, as a result of which farmers can monitor what they are planting and where their seeds are placed on a real-time basis (Johnston, 2014; Pattinson and Johnston, 2016; Cukier and Mayer-Schoenberger, 2013; Noyes, 2014). IoT in agriculture not only helps improve productivity and profitability but also paves the way for drastic changes in farm management and sustainable agriculture practices (Kite-Powell, 2016). For instance, smart farming tools for site-specific applications of fertilizers, GPS mapping, and accurate yield predictions have the potential to boost sustainable farming practices and enhance profitability (Walter et al., 2017).
In the midst of rapid population growth, dietary shifts, resource constraints and dietary changes, there is a growing emphasis on efficient management and optimal usage of inputs such as fertilizers through data-driven farming decisions (Lee and Choudhury, 2017). Such trends are compelling more farmers to use versatile IoT tools improve crop output, lower livestock losses and reduce water usage across a diverse range of agricultural operations (Guerra, 2017). Cloud-based IoT tools and sensors help livestock farmers monitor swine, cattle, broiler and milk production.
For instance, collar units and ear tags provide...