Artificial intelligence (AI) has made its way across various fields like sales, medicine, architecture, marketing and finance. And, agriculture being a major contributor to the Indian economy, is not untouched. As traditional processes used by farmers were not enough to satisfy the growing food requirements, it became necessary to bring automation in agriculture too. These days irrigating, securing and fertilizing crops are done using devices based on advanced technologies like AI, machine learning (ML), and internet of things (IoT). Read on to know more…
How is AI used for sowing seeds?
Artificial intelligence has allowed us to create optimal models for analysing the climate and forecasting weather. Bio-sensors (IoT) have even made it possible to check the moisture and fertility of the soil. Raw data is collected and various methods like Bayesian Networks and neural networks are used to predict the weather instead of using basic linear regression models. Notably, neural networks can compute and predict with non-linear dependencies of past weather trends. So, for necessary commodities like rice, wheat and maize, AI can be used to sow the seeds at the correct time as they mainly require heavy rainfall to grow and are usually grown during the monsoon season.
How is AI used for irrigation?
Watering crops at the right time is necessary in order for the crops to produce the correct yield. Watering on a large scale by a few farmers became a cumbersome process as they were not enough in number. Smart irrigation systems were introduced. These systems mainly have two components, a machine learning model to compute the amount of moisture in the soil and the implementation of hardware using IoT devices.
To design one, all you need are the following:
- A machine learning model to determine the level of moisture in the soil
- An IoT device having the following components:
NodeMCU – 1
Moisture sensor -1
Water pump – 1
Battery – 1
Socket – 1
Plug (2-pin) – 1
Switch – 1
Data cable and system for programming (e.g. Arduino IDE)
The code is written on NodeMCU and the hardware is implemented using Arduino programming.
How is AI used for crop security?
Securing crops can be done in many ways like analysing the weather and climate or setting up motion-detecting electrocuting fences. A motion detection security system can not only protect the yield from animals but also trespassers. A security system for crops based on AI uses mainly Python and OpenCV (Open Source Computer Vision Library). This allows the programmer to segment the background and the foreground, individually being captured on a single camera to detect any change in frames. In case there is a sudden change in frames, the AI will proceed with the necessary repercussions (example: electric fence activation and activating alarms).
How is AI used in crop yield and price forecast?
The fluctuation in the price of the yield is the biggest thing that a lot of farmers worry about. Vegetables like green beans have a very short shelf life, which leads to irregularities in the pattern of production. AI startups and companies are using weather and satellite images to monitor the health of crops. With the help of big data, artificial intelligence and machine learning, models can be built to detect pests and diseases, improving crop health by providing real-time analysis. Models are also built to provide real-time analysis on crop yield, output, the pattern of production in yield and also price forecast using previous data.
How does AI solve the shortage of skilled labour?
With a really small number of people entering farming, most farms face a shortage of skilled labour. Originally, farms used to require a large number of workers, most of them working seasonally to harvest crops. However, as humans have moved from an agrarian to an urban and suburban society, there has been a shortage of workers. This shortage was mitigated with the help of AI bots. These bots are used in many ways. They can produce yield at a volume higher and attain it at a faster pace than human workers. The bots perform tasks more accurately to identify and eliminate liabilities (example: an area of weed) and diminish costs for the farms by having a workforce that can possibly work 24 hours without having to take breaks.
Chatbots have also been in development. These chatbots will answer direct questions to assist farmers with what to do on their fields or pouring the right amount of water for example by distinguishing which patch of land is more dry or wet.
Companies Offering Services to Improve the Agro-based Industry in India
- NinjaCart – This company was started in 2015 to connect farmers to retailers directly, and aimed to provide fresh produce supply. They use data science and artificial intelligence to figure out solutions to problems like food wastage, inefficient supply or distribution, and low quality of food. They also use business intelligence tools to predict prices and neural networks to forecast the demand, causing a reduction in the wastage of food.
- Aibono – Founded in 2014, Aibono uses data instruments and predictive analytics. With a total funding of $5.5M USD now, it aims to improve processes to help farmers with their yield production. Aibono syncs real-time production with real-time consumption of fruits and vegetables having low shelf life by using predictive analysis, precision farming, and harvesting at the right time.
By and Large
With the increasing population, the demand for basic commodities is growing exponentially. The shortage of workers in the fields would eventually lead to farms being shut down and eventually facing a food crisis in the future. Automation in agriculture using artificial intelligence, machine learning and IoT has let humans steer away from that gruesome future and into a fruitful one.