Introduction
According to UN food and agriculture organization the world needs 70% more food in 2050 due to the exponential growth of the world population. Adoption of internet connectivity solutions has been triggered to reduce the need of manual labour. Problem with the traditional sensor technology 1) we were not able to get the live data from the sensors, 2) The sensors used to log the data into their attached memory. IoT in Agriculture introduced more advanced sensors that are now connected to the cloud via cellular/satellite network. It gives the real-time data from the sensors, making decision making effective. IoT based Smart Farming monitor the field in real-time.
About IOT
The internet of things, or IoT, is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. A thing in the internet of things can be -- a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors are any other natural or man-made object that can be assigned an Internet Protocol (IP) address and is able to transfer data over a network.
History of IOT
A group of students from the Carnegie Melon University in 1980s created a way to get their campus Coca-Cola vending machine to report on its contents through a network in order to save them the trek if the machine was out of Coke. They installed micro-switches into the machine to report on how many Coke cans were available and if they were cold. In 1990, John Romkey connected a toaster to the internet for the first time. Kevin Ashton, co-founder of the Auto-ID Centre at the Massachusetts Institute of Technology (MIT), first mentioned the Internet of Things in 1999. He used the phrase as the title of his presentation for a new sensor project he was working on and it stuck from there. World’s first refrigerator connected to the IOT was introduced by LG Electronics in 2000.
Figure 1: Structure of IOT
Smart Farming
"Smart farming" is an emerging concept that refers to managing farms using technologies like IoT, robotics, drones and AI to increase the quantity and quality of products while optimizing the human labour required by production.
Figure 2: Different components of Smart Farming
Internet of Food & Farm 2020 (IoF2020)
The project Internet of Food & Farm 2020 (IoF2020) explores the potential of IoT-technologies for the European food and farming industry. IoF2020 is part of Horizon 2020 Industrial Leadership and supported by the European Commission with a budget of EUR 30 million.
The aim of IoF2020 is to build a lasting innovation ecosystem that fosters the uptake of IoT technologies.
For this purpose, key stakeholders along the food value chain are involved in IoF2020 together with technology service providers, software companies and academic research institutions.
IoF2020 (Internet of Food and Farm 2020) brings together 70 partners from 16 European countries with the objectives to accelerate adoption of IoT for securing sufficient, safe and healthy food and to strengthen competitiveness of farming and food chains in Europe.
Agriculture-as-a-service (Aaas) architecture
The existing agriculture systems are not able to fulfil the needs of today’s generation due to lacking in important requirements like processing speed, data storage space, reliability, availability, scalability etc. To solve the problem of existing agriculture systems, there is a need to develop a cloud-based autonomic information system that delivers Agriculture-as-a-Service. The services of AaaS have been divided into three types: SaaS (Software as a Service), PaaS (Platform as a Service) and IaaS (Infrastructure as a Service). In SaaS, a user interface is designed in which users can interact with system. In PaaS is used as a scalable cloud middleware to make interaction between cloud subsystem and user subsystem. In IaaS, an autonomic resource manager manages the resource automatically based on the identified QoS requirements of a particular request.
Subsystem of AaaS
1) User Subsystem
This subsystem provides a user interface, in which different type of users interact with AaaS. Nine types of information of different domains: crop, weather, soil, pest, fertilizer, productivity, irrigation, cattle, and equipment. Users are in three categories: i) agriculture expert, ii) agriculture officer, and iii) farmer
2) Cloud Subsystem
This subsystem contains the platform in which agriculture service is hosted on a cloud. Details about users and agriculture information are stored in a cloud. The information is monitored, analyzed and processed continuously by AaaS.
Figure 3: Agriculture-as-a-Service architecture
Application of IOT in Agriculture
1. Application of Sensors
Sensor is a particular device or module that helps us to understand the actual condition in field. It helps us to use scarce resource like water, fertilizer scientifically with optimum concentration. Wireless Sensor Network (WSN): It consists of various sensors/nodes which are integrated together to monitor various sorts of data. Smart Sensor Technology (SST) regulate the rates of fertilizer, seed and chemicals. Sensors is important aspect in climate change mitigation and agricultural sustainability.
Figure 4: Application of Different sensor in Agriculture
2. Application of automation and robotics in relation to IOT based smart farming
Farm automation is a variety of tech innovations in traditional farming to optimize the food production process and improve quality. As of now, advanced farming technology can be an essential part of the farmer’s daily work. Some Robots and autonomous machines-
Seeding and weeding robotics
Robots for planting are focused on the field’s specific area, and they work with great precision. This type of farming robot uses artificial intelligence and computer vision, which allows for a reduction of pesticides in the field and, subsequently, the production of high-quality food.
Automatic irrigation
Robot-assisted irrigation systems contain a big part Subsurface Drip Irrigation (SDI) system plus special sensors. SDI – it controls the amount of water that is used, and at what time the plants receive it. The RAPID (Robot-Assisted Precision Irrigation Delivery) project offers farmers a cost-conscious solution.
Harvest automation
The first commercial company specializing in apple harvesting. Harvesting of crops/fruits requires the use of dedicated sensors that are efficient for unambiguous, and precise details of that particular fruit.
Internet of Things-Based Tractors
These Internet of Things-based tractors provide a better precision along with the reduced error, mainly when spraying pesticide. HELLO TRACTORS has designed a cost-efficient monitoring device that can be mounted to any ordinary tractor and that device provides software and analytical tools.
3. Application of IOT based drones in smart farming
Drones or Unmanned Aerial Vehicles (UAVs) are flying devices that are autonomously programmed or remotely controlled, either by a remote control or a ground station, and are categorized as networked robotic technologies. It reduces the use of human labour in surveying crops and can cover up to 10 times more ground in a given amount of time. Drones with machine vision and specialized algorithms can be used to find yield limiting problems.
Figure 5: Application of Different sensor in Agriculture Drones
4. Application of remote sensing in IOT based smart farming basic principle
The sensor typically measures the electromagnetic radiation that is either reflected or emitted by the target. Different objects based on their structural, chemical, physical properties reflect or emit different amount of energy in different wavelength ranges of the E.M.S. The sensors measure different amount of energy reflected from that object. IoT finds a wide usage in data acquisition, processing and interpretation in many fields of interest, and Remote Sensing is one of them, being an important area of signal processing research and studies. IoT for Remote Sensing Applications is another exciting area of interest where IoT empowers smart systems to detect, sense and analyze various parameters that assist in a robust monitoring of the environment.
Figure 6: Application of Remote Sensing in Agriculture
5. Computer Vision and computer imaging in IOT based Agriculture
Humans interpret the real world with a vision processed by their brains to make sense of the surroundings. Computer vision is the branch of computer science that aims to provide a similar outcome using a computer system or machine. With computer vision, machines can accurately identify and detect objects, analyze and make meaningful interpretations out of a sequence of images. It is a subfield of Artificial Intelligence
Figure 7: Computer Vision Application in Agriculture
6. Livestock monitoring using IOT
Livestock monitoring using IoT helps to monitor the health and vitality of livestock in real-time, enabling farmers to quickly treat animals and prevent the spread of illness or disease.
Monitoring health levels
Using a wearable collar or tag, battery-powered sensors monitor the heart rate, respiratory rate, blood pressure, digestion level, and other vitals can help farmers stay up-to-date with their cattle’s health levels.
Monitoring reproductive cycle
A connected IoT device can help to monitor and measure a cow when it goes into heat, as cows can be in heat for around eight hours. The same device can also notify the farmer when the cow goes into labor thus making the calving process safer. IoT-enabled monitoring completely removes the need of supervising cows manually for the calving process and promotes safer and successful births.
Location tracking
Livestock monitoring solutions can use GPS tracking to gather and store historical data on preferred grazing spots. IoT wearables track the movement pattern of animals.
Maximizing livestock livelihood
By monitoring cattle behaviour, a farmer can easily identify if the cow needs to be milked at that time. Not just that, IoT devices can also help to measure the milking amount and speed. They can also track the amount of food a cow consumed and the number of steps it walked in a day.
Figure 8: Livestock monitoring using IOT
7. IoT Based Smart Greenhouse
Greenhouse farming is a technique that enhances the yield of crops, vegetables, fruits etc. Greenhouses control environmental parameters in two ways; either through manual intervention or a proportional control mechanism. However, since manual intervention has disadvantages such as production loss, energy loss, and labor cost, these methods are less effective. A smart greenhouse through IoT embedded systems not only monitors intelligently but also controls the climate. Thereby eliminating any need for human intervention. The Different sensors that are used to measure the environmental parameters to the plant requirement for controlling the environment in smart greenhouse are as follows:
Soil Moisture Sensor
Light Sensor
Humidity Sensor
temperature sensor
Light Dependent Resistors LDR) sensor
Figure 8: Structure of a smart green house
By Aishik Sadhukhan & Udit Debangshi
Institute of Agriculture, Visva-Bharati, Sriniketan, West Bengal (731 236), India
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