The United Nation’s Food and Agriculture Organization (FAO) predicts that by 2050, the world population will rise by 2.3 billion and, to effectively feed that population, our food production needs to increase by 70%. According to research conducted by the University of Minnesota, production for essential crops—such as maize and rice—is currently increasing by increments of about 1% per year. If our current rate holds, the world will fall well short of the 70% goal, making increasing food production one of the biggest challenges our generation will face in the next 40 years.
So what can be done to meet this growth? One suggestion is to dedicate more land to farming. Although simple in its directness, this may not be viable in the long run, as a population boom and rising sea levels increase land value for housing and urbanization. More land also means more water supply, and in recent years, certain markets (like California) have actually seen declines in agricultural yield from droughts as climate change causes water shortages and makes agricultural planning unpredictable.
On the other end of the spectrum, the emergence of new production methods, such as lab-grown meat as well as vertical and insect farming, hold the potential to solve issues related to resource and supply limitations. However, these methods face infrastructure and monetary challenges that require policy changes to effectively scale. In the cases of lab-grown meat and insect farming, education and acceptance will also see a slow progression.
Looking back, agriculture saw massive gains in crop yield with the introduction of farming equipment such as tractors, pesticides, and better seeds. Now, farmers are turning to IoT. Companies such as DuPont and Monsanto, alongside a number of startups, are investing millions in creating connected farming equipment, consisting of massive sensor networks that gather environmental data to free analytics platforms in order to research three critical questions: how can we increase yields, reduce risk, and be profitably eco-friendly?
There are a couple of necessary components that farmers need to know in order to maximize crop yields: when to plant, when to water, and what the condition of their soil is like. The challenge is that these factors vary drastically from acre to acre, affecting yields between fields by up to 75%. Farmers have traditionally relied on gut feelings and experience to maximize their harvest. In recent years, aided by the use of IoT sensors and data analytics, precision farming has emerged.
Precision farming uses distributed sensor networks and satellite imaging to monitor key factors such as temperature, moisture, soil nutrients, and historical data of crop growth. These metrics inform farmers of the variability in their fields with unprecedented granularity, allowing them to fertilize where needed, plant more in underutilized spaces, and accurately predict when to plant and harvest. John Deere and other farming equipment manufacturers are integrating with these networks to automate tasks, such as land preparation and seed sowing, to help optimize farming practices. Although it’s still too early to tell what long-term improvements precision farming can bring, in some cases, it has helped increase yield by 50%.
Furthermore, by sharing their data on platforms provided by companies such as DuPont and Monsanto, farmers can gain access to predictive yield analytics that factor in potential improvements farmers can make in the off season and share foresight into weather forecasts. This also grants access to experts who analyze and offer advice for how to further increase land productivity and manage it moving forward.
Even today, disease and pest breakouts are some of the biggest risks faced by farmers. The most common preventative measures for commercial farms include the application of pesticides and herbicides. Companies like Dolphin Engineering and their PreDiVine system are looking to change this practice. By analyzing data collected by many of the same sensors employed for precision farming—such as temperature, moisture, and rainfall—PreDiVine creates models of microclimates within fields and uses research on pest and disease incubation to predict outbreaks.
These systems could also predict weed outbreaks in the future, allowing farmers to change their pest and weed prevention strategy; instead of mass spraying chemicals, they can target problematic areas. An additional benefit is that farmers who use natural seeds can implement such a solution to keep their product organic, increasing the value of their yields. Data about microclimates and soil conditions could also allow farmers to mitigate business risks, by allowing them to diversify and grow various crops that maximize yield in different parts of their field, while restoring soils naturally through perennial composting.
IoT systems can offer similar insights and benefits for dairy farms and livestock, using cow-monitoring systems like the one from SCR Dairy. These devices use motion sensors, GPS, and microphones—the same technology found in fitness trackers—to give farmers real-time alerts about livestock health, including whether their cows are in heat, in labor, or simply not eating as much. This significantly reduces labor needs and enables livestock farmers to carefully monitor herds of hundreds of cows from an iPad.
The combined data of where seeds were planted or cows have been, combined with disease-predictive algorithms, could provide significant breakthroughs in food safety. The ability to trace disease outbreaks and study the conditions in which they emerged could lead to better understanding causes and effective quarantines, eliminating widespread food waste.
Profitable Eco-Friendly Farming
Pesticides, herbicides, and fertilizers, along with being the largest sources of pollution from agriculture farming, also have the highest variable costs for farmers. But being able to make effective changes often involves slowing or even endangering production, thus hindering the adoption of more sustainable farming methods.
Education around the eco-friendly and cost-effective results of implementing IoT devices on farms is essential for making industry professionals willing and ready to adopt these new technologies. For example, by predicting soil needs in advance, farmers can plant legumes or other natural crops that maintain soil efficacy. This drastically reduces the use of artificial chemicals and, by proxy, farmers’ operational costs. Other companies, such as Smart Watering Systems, are linking information from weather forecasts to create automated irrigation systems, reducing a farmer’s water use by 30–70% and significantly minimizing their environmental impact, while also providing huge savings. By and large, the same subset of connected sensors are enabling new farming methods, crop and animal health monitoring, and rendering eco-friendly solutions more cost effective. As this set of hardware becomes ubiquitous, farming of the future is shaping up to be more of an exercise in interpreting data and seeing who can provide personalized insights to maximize production, profitability, and long-term growth. DuPont, Monsanto, and other companies that provide ongoing services and value to their consumers in the form of data analytics will ultimately compete to control data from users.
Farms are on their way to becoming entirely automated. As mobile devices continue to improve and are capable of receiving, analyzing, and adjusting behavior accordingly in real time, farms are becoming, in some respects, smart-farm hubs. This integration, facilitated by IoT, could create truly intelligent, autonomous farms—making it easier to produce what we need for looming food shortages.
The impact that IoT and data analytics are having on agriculture demonstrates how they can help solve problems in other industries that are repetitive, inconsistently face the same issues, span large areas, and require both people and machines in order to thrive. Both construction and mining, for example, have similar characteristics to agriculture and are already adopting IoT. Using data and machine-to-machine communication, construction companies are improving the transition time on sites, allowing them to build faster. In mining, distributed sensors are analyzing soil and rock samples to make drilling decisions for long-term planning. These are all indicators of IoT being deployed on large scales—moving out of the smarthome to become the tools that will change the way we mine, build, and feed more than 9 billion people.