Smart Agriculture using IoT
Another very important domain in the internet of things is the agricultural domain. IoT is responsible for modernizing the agricultural field by using proficient methods and instruments to manage crops, soil and animals. This in turn has led to decrease in the waste generation and a phenomenal increase in productivity. This is smart agriculture using IoT.
Some of the applications of IoT in the agricultural domain are as follows:
- Sensors to monitor and track the status of crops and insects
- Drones for monitoring the livestock such as hens
- Automated water pumping systems to water the crops according to convenient times
- Machines for performing route operations and ensuring proper functioning of systems
What is smart agriculture?
Smart agriculture is a newly introduced concept. Majority of farmers and agricultural experts are new to this concept. Smart agriculture involves the use of smart technologies such as automated machines, sensors, actuators, drones and security cameras to control and operate agricultural lands and animals. The motive is to increase the quality and quantity of agricultural goods at the same time keeping in mind the cost and energy usage.
What is a smart farm?
A farm which is managed using smart technologies and modern forms of communication is termed as a smart farm.
The various of technologies farmers use in smart farms are:
- Sensors for soil, water, moisture and humidity control
- Software to diagnose plant and animal disease, to learn and treat the disease.
- Connectivity using LoRa or cellular networks
- Managing and tracking locations using GPS and satellite
The smart farms are completely operated by automated tools and robotics in such a manner that the farmer does not even have to step on the field. The cost of manual labour reduces due to smart farming. IoT integrates and connects the entire farm to improve quality and quantity of crops and other produce.
Smart farming and traditional farming
Traditional farming methods used old and outdated farming methods. Manual methods are used to monitor the soil and manage the livestock. These methods are time consuming and expensive. It is very difficult to detect outbreaks at an early stage.
Smart farming uses modernised methods and IoT based technology to manipulate and manage the agricultural yields. It includes the usage of Geo locations, GPS tracking, sensors and drones to monitor the fields, crops and cattles.
IoT based smart farming cycle
Data is the center of any IoT based technology. In order to ensure optimization, smart farms must form a continuous and constant cycle that collects and analyzes data to perform the next set of actions. The following is an example of a smart farming cycle:
- Observation: sensors are used to sense the surroundings and collect information about the soil, temperature, humidity and so on.
- Diagnostics: the information collected from sensors are sent to IoT based cloud platforms for data analytics.
- Decisions: based on the analysis done the farmers make relevant decisions to generate better outputs.
- Actions: when the tasks are operated the cycle repeats itself from the beginning.
IoT solutions for agricultural problems
IoT offers solutions to many of the agricultural problems. The most important IoT based solutions are precision farming and automated farming.
Precision farming
Precision farming is a modern approach which makes use of precision values to get an increased amount of yield and produce. It obtains accurate data and precision amounts about the agricultural lands. As a result of this, plants and animals get the exact amount of input they need as decisions are made for each plant or animal rather than the entire produce or cattle.
Precision livestock farming
The main target of PLF is to monitor, control and manage individual animals by using precision techniques that generate accurate data about individual cattle. Precision technology measures and collects data about the livestock 24 hours every day. The farms are notified in case something goes wrong with any farm animal. This allows the farmers to respond quickly to prevent disease outbreaks or any other setbacks.
Automation in smart greenhouses
Smart greenhouses are controls with devices such as temperature sensors and actuators. These devices capture and send information 24/7. This information is fed to clouds that later store the information in servers for future needs. Once the performance analysis is done, lighting control and spraying activities are managed accordingly.
Agricultural drones
Farmers use drones to collect insight and real time information about crops and animals on the barns. The drones monitor the entire field from the sky and send alerts to the farmers in case of suspicious activity. These drones are also placed for security purposes.
Third green revolution- future of smart farming
Smart agriculture is taking over farms of all sizes by rapid speed. It is becoming a part of a movement that is known as the third green revolution. It involves the use of modern IOT devices such as security cameras, sensors, drones and actuators to manage agricultural yields. Smart agriculture has increased in profitability by providing help to both farmers and consumers.
IoT in agriculture
The world’s population is growing by large percentages. Agriculture needs reforms to feed the world in large quantities. The internet of things allows the integration of technology with agriculture to provide better quality food, management, monitoring and control.
How automation and robotics help?
As the population rises the increase for food also certainly rises. In order for the demands to be met, we require automated methods that reduce the cost spent on manual labour. We also require methods that reduce the time taken to cultivate produce. All of this must be done keeping in mind the health of the individuals that will consume the produce.
Semi automatic robots could be placed in the fields in order to detect insects and pesticides to stop their growth at an early stage. These robots can also overlook heavy vehicles. The farmers can easily control these operations from the comfort of their homes.
Processes in smart agriculture
1. Data collection: farmers place sensors in the farm to gather information about the moisture levels in soil and so on.
2. Diagnostics: the data is then sent to clouds for processing. The data is interpreted to generate weighted outputs.
3. Decision making: based on the processed data the next step is taken with utmost care and precaution.
4. Action: once the decision has been made, it is time to take necessary action towards fulfilling the goals.
Smart irrigation system
Smart irrigation systems check the water levels in the water lanes that farmers make. They involve the use of raspberry pies and Arduino boards. The main processing unit is the raspberry pi and the arduino board is for each of the water lanes.
The arduino boards are capable of connection to various sensors that are a part of the water lanes. These sensors collect vital information such as moisture and hydration levels of the soil.
In case any water lane does not meet the level that the farmer specifies, the Arduino boards send signals to the Raspberry Pis that then alert the farmers to take the necessary steps. The farmers interact with application to activate the relays that send water to the lanes as per the specified criterion. The smart irrigation systems can be seen as gate controlled systems that adhere the gates open only when the moisture content is less.
In case the moisture levels go beyond the limits it sends another signal to the raspberry pi to stop the pumping. This system leads to efficient uses of resources and reduction in water usage. Smart systems such as these increase productivity in agriculture.
Challenges in the modern agricultural city
Given below are some of the challenges farmers face with the modernisation of the farming industry:
- Lack of labour and human resources
- Global warming and greenhouse gases
- Manual intervention at a larger platform
- No proper monitoring systems
- Challenges in processing the large amount of non uniform data
IoT analytics in agriculture
The data incoming from sensors is sent for further processing and analysing. Smart farming integrates machine learning and predictive analysis to help farmers deal with natural calamities such as droughts and landslides.
Application of smart agriculture
1. Drone-based uses
Smart farming also involves the deployment of drones to monitor areas from a remote location. Drones can reach places humans cannot reach. They are also capable of collecting information and data. They can send users data regarding soil, livestock, water levels and in addition help in the prevention of burglary attempts, crow attacks and so on.
2. Real-time crop monitoring
Temperature sensors, light sensors, motion sensors and various other smart sensors allow for retrieving real time updates about the crops. The farmers can remotely check on the status of the crop to ensure smooth functioning.
3. Livestock management
Sensors and smart cameras can count the number of animals such as hens and pigs on the farm. Sensors can also obtain health conditions about the animals on the farm. This helps in the early detection of flu breakouts and allows farmers to take necessary actions more quickly.
4. Tank level monitoring
Iot allows the remote mounting of water levels in huge tanks. It alerts the authorities when water levels fall below the average level in the tanks.
5. Smart greenhouse solutions
Greenhouses ensure that the plants meet the required level of oxygen levels. However, this procedure requires continuous monitoring and outside intervention. But a smart greenhouse uses iot monitors and sensors that sense the atmosphere to send vital information for further analysis. This is a reliable and efficient procedure that curbs the level of harmful pollutants in the environment to a large extent.
6. Data analytics
Cloud and IoT platforms play an important role in smart agriculture systems. Sensors are the main source of data collection. However if there is no proper mechanism to analyse the data then the information has no uses. The data undergoes predictive analysis and the cloud generates back a necessary action on the basis of the inkling data.
7. Infrastructure requirements
In order to implement smart farming the farms require some basic infrastructure such as stable internet connection, hardware maintenance cost, huge investment on drones and sensors, a well trained staff and stable power connection.
Summary
In this article we looked in detail about the topic, smart agriculture. We learnt how different it is from traditional farming and its applications ranging from real-time crop monitoring to smart greenhouse solutions. We hope the article was easy to understand.