According to the FAO, global population will reach 9.7 billion by 2050, making it necessary for global food production to increase by up to 70% in the next 30 years. It is perhaps in response to this growing demand that indoor farming has been gaining so much attention.
The indoor farming technology market was estimated at $23.75 billion in 2016 and will grow to $40.25 billion by 2022. Rising temperatures and more frequent droughts induced by global warming are fuelling the trend. Traditional farming was also hard hit by the COVID-19 epidemic, which resulted in border closures, restrictions, and supply disruptions.
Indoor farming allows you to do away with the inefficiencies and unpredictability of traditional agriculture. It enables you to control growth conditions better; it also tends to use less water and pesticides, makes crops less sensitive to climate change, and generates more consistent harvests.
Indoor farms also allow us to use land more productively by planting crops in vertical layers and keeping plants safe from unwanted insects, animals, heavy downpours, drought, and other damage. We can create artificial rains and even provide more or less sunlight depending upon the plant’s requirement. For all these reasons, it is increasingly viewed as a viable solution that combines the best of technology and nature.
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Infusing indoor farming with Data analytics solutions allows farmers to monitor and control the environmental factors that affect plant growth. We can use IoT sensors to monitor the environmental variable continuously and use this data to make informed decisions. Using IoT analytics services, we can keep a close watch on all the variables in the farm and thus reduce labor costs.
Smart indoor farms are essentially indoor farms that rely on IoT devices. This farm is a closed structure with IoT sensors like humidity sensors, temperature sensors, soil moisture sensors, and actuators that remotely control plants’ irrigation.
Soil moisture sensor: It has a fork-like structure with exposed conductors and acts as a variable resistor. When inserted into the soil, the sensor’s conductivity varies depending upon the water content in the soil. When the water content is high, the conductivity increases; hence resistance is low. When the water content is low, the conductivity decreases, and the resistance increases. Having this data helps us better understand the moisture content in the soil.
Humidity sensor: It contains a capacitor with two electrodes with a substrate filled in between them; this substrate can hold moisture as a dielectric between the electrodes. The change in humidity levels will alter the capacitance value, which is measured and processed into the digital output.
Temperature sensor: This sensor contains a negative temperature coefficient thermistor, which acts inversely to the change in temperature. Hence, an increase in temperature will decrease resistance and vice versa.
We can also use sensors to detect soil temperature, pH, and NPK and acoustic sensors to detect pests by the sound they make as they pass.
Sensors like humidity, temperature, and soil moisture sensors will collect data in real-time from the environment/farm and send this data to the cloud. A mobile application or website then fetches this data, and the user can view the farm’s current status as a visual. The visualization helps the user to understand the current condition of the plants on the farm and use this knowledge to make informed decisions.
• Depending upon the soil’s moisture content, the farmer may decide to water the plants more/less frequently.
• By analyzing the data, the user will understand if the artificial environment provided for a particular plant is apt or not. For instance, if the crop is nearing harvest, the farmer might decide to switch the humidity and temperature levels of the environment or farm to produce the best yield.
Indoor farming holds a lot of potential for the future, as it helps us closely monitor the plant’s growth and provide ideal conditions by manually adjusting environmental variables.
The applications are endless. For instance, by placing obstacle or motion detection sensors in the field, we can detect pests, insects, and rodents on the farm. We can use drones to fly around the farms and capture images of the plants; by using advanced ML/DL techniques, we can detect diseases in the plants.
The data we get from the farms can be stored and analyzed, and by performing data analytics, we can determine the best parameters for a particular plant. For example, for a tomato plant, we would be able to discover the optimum water, humidity, temperature, and other environmental parameters that produce the best yield. By maintaining these ideal conditions, we can maximize production over time.
The ‘smart’ IoT farm will thus maximize crop production and serve as a data factory that improves crop quality over subsequent seasons.
Learn how IOT analytics can enhance efficiency of manufacturing & production sectors: Enhance Efficiency in Manufacturing and Production with IoT & Advanced Analytics
Despite the high initial setup costs, ongoing maintenance costs, and the demand for skilled labor, indoor farming is here to stay. The product’s productivity and quality will help investors get good returns on their investment.
With Indium’s Data analytics solutions capabilities, you can now gain IoT analytics for your business too!
By Uma Raj
By Uma Raj
By Abishek Balakumar
Vasanth Williams is an Automation Engineer at Indium, focusing on end to end IoT testing . He holds B.Tech in Computer Science and has also published paper in IEEE Xplore on the topic IoT based Smart Home. He thrives to find innovative ways to Automate IoT testing.