Part of:Explore IoT use cases that improve sustainability
Agriculture IoT promotes sustainable practices
Agricultural organizations can adopt IoT in their farming practices to not only optimize their production, but also to improve their sustainability with precision agriculture.
The smart agriculture industry, also called precision agriculture, seeks to address the global necessity to increase sustainable practices in farming, improve crop yields and optimize agricultural resource use through IoT technology.
The most prominent reason for this need is population growth. The current global agricultural system is under constant increasing pressure to supply more food: The world population will approach 8 billion by 2023, according to the United Nations, and is expected to surpass 10 billion people in the next 40 years.
The agricultural industry must also attend to a vast public awareness that the world requires improved stewardship of the global environment, including air, soil, water and climate. In agriculture, such stewardship refers to sustainable practices that are nature-positive or regenerative, nondepleting and nondestructive to the ecosystem.
IoT can transform the agriculture industry into nature-positive precision agriculture through combinations of technology advancements in sensing and communications. These advancements have led to analytics-informed management and farm automation applications that can reduce crop risk, improve production yields and preserve resources better than ever before.
Optimizing yields using automation
Agricultural organizations focused on outdoor farming can apply IoT technology to optimize their production using automation in many ways. Modern farm equipment networked with wireless communications and GPS capabilities can precisely and accurately control where seeds are planted, a practice known as variable-rate seeding.
IoT can transform the agriculture industry into nature-positive precision agriculture through combinations of technology advancements in sensing and communications.
Research has shown that variable-rate seeding significantly improves crop yield per acre and improves planting efficiency by minimizing seed waste. Tractors can control planting depth and spacing to optimize growth for different crops or different conditions in the soil. Equipment of all types can be made aware of other machines and their mechanical paths through a field, avoiding damage to crops and assuring more effective conditioning and maintenance of the field over time.
Improving resource efficiency using automation
Precision farming depends on the use of IoT sensing from a variety of technology-based resources. Agricultural organizations can use electronic mapping of an agricultural space combined with historical data from soil sensors, drone cameras and mobile farm equipment GPSes to inform seasonal crop selection and rotation. Weather and real-time soil sensor data also inform water management. Farms can use multiple methods for watering -- but research has shown that precision water delivery, such as automated trickle or subsurface methods, works best. Precision water delivery reduces evaporation, improves soil moisture content and delivers water most effectively in response to real-time weather conditions. Farmers can also use data from sensors in the ground to develop a model of soil fertility in reaction to different crops and conditions over time. The model could include effective fertilizer and soil bacteria management for improved nitrogen, phosphorous and potassium uptake, all of which can maintain land health in the long term.
Automation has an advantage over manual equipment when it comes to optimizing fuel use, resulting in a direct reduction of greenhouse gas emissions. Fuel optimization is essential because fossil fuel still powers the majority of farm equipment. Some automated tractors can manage the engine's rpm to most effectively work the field -- even with changing slopes and rougher terrain -- further improving fuel efficiency.
Agricultural supply chain improvement and IoT
Automated drones and sensing equipment can monitor crops in real time, using available data to help identify changing conditions for the supply chain. Software with AI-based monitoring of drone footage can positively identify pests and disease, reducing crop risk and helping to inform a fast response. Agricultural organizations can use data analytics from visual drone data and other farming equipment cameras to assess production in terms of growth rate, estimated wet weight, dry weight and other data critical to improving the efficiency of downstream distribution chains. Looking upstream, farmers can identify the most effective use of water, fertilizer and fuel for equipment based on the crop and soil conditions in combination with predicted weather. These data insights can help focus supply chain activity and further improve the industry's efficiency as a whole.
Precision agriculture and indoor farming
Indoor farming is the practice of farming in a greenhouse. However, unlike traditional greenhouses that rely on the sun for energy, modern indoor farming uses IoT technology to produce agriculture at a fraction of the space and resources used by conventional outdoor methods. Vertical farming -- or growing plants vertically in a warehouse setting and using automation to tend to plant and environment health -- has shown significant progress. Indoor farms use artificial light from LEDs for lighting optimization and precise photoperiod control, a practice that can ensure a crop gets the right color spectrum of light and the right amount of light in a day at the right intensity to maximize crop yield over short time periods. Indoor farming can also use hydroponic and aeroponic water delivery, eliminating the need for soil. Today, nearly all commercial indoor farming uses precise water, nutrient and environment management as well as pest and health monitoring via networked sensors and software systems.
