According to an article published by the United Nations, the human population is predicted to reach 9.8 billion people by 2050. What it means is that we need to find an effective way to provide food and supplies to the growing population while also keeping sustainability in mind.
As impossible as it sounds, there seems to be an effective solution to the challenge. Smart farming has already started taking place in the agriculture industry across the globe, and more and more farmers are implementing technology to make farming more efficient and sustainable.
Defining Smart Farming:
Smart farming implies 1) providing the agricultural industry with the infrastructure that is needed to leverage the use of technology and 2) using this technology to increase the quality and quantity of products while reducing costs and resources. In simple words, smart farming is about using technology to improve farming processes, like crop monitoring or greenhouse management.
Since “technology” is a rather broad term, let’s look at specific examples of what exact technological advancements are used in smart farming:
● Internet of Things: is used to collect real-time data;
● Sensors: are used in IoT systems to capture the data (i.e., humidity, soil acidity);
● Connectivity: needed to create a single digital ecosystem and can be cellular or LoRa;
● Location tracking: includes GPS and satellite location tracking;
● Robotic Process Automation: automates mundane processes;
● Artificial Intelligence and machine learning: used to automate and elevate processes;
● Big Data and analytics: helps farmers make accurate data-driven decisions.
As you can see, smart farming involves a wide array of technologies, often working in conjunction to create a streamlined and centralized workflow. If you need a real-life example, SoftTeco, a machine learning consulting company, has worked on several smart farming projects, including the one on greenhouse automation and the use of computer vision to detect the health of crops. Now, let’s look at how exactly smart farming benefits agriculture, in addition to making it more effective and sustainable.
The Benefits of Smart Farming:
Even though smart farming is just starting to pave its way to the agriculture industry, it will without a doubt become a common thing in the near future. Here are all the benefits that it brings:
● Increased crop yield and better crop health due to smart, 24/7 monitoring;
● Reduced ecological footprint due to smart allocation of resources and reduction of energy consumption;
● Better resource management and allocation combined with decreased operating costs;
● Improved equipment maintenance due to the use of ML and computer vision;
● Increased efficiency of operations through automation and digitization;
● More accurate risk forecasting and prediction of demand;
● Remote field monitoring with the help of automated drones.
The Role of IoT in Smart Farming:
While smart farming involves an array of technologies, IoT is often referred to as the driving force of smart farming. This is due to the fact that IoT connects multiple machines and devices and allows real-time data collection, which is later used for analytics and decision-making.
The IoT-driven smart farming follows a certain cycle, which consists of 4 main steps:
● Observation: sensors record the observational data, such as soil acidity, temperature, humidity, etc.
● Analysis: the collected data is sent to the server where it is analyzed in order to determine the condition of the examined subject.
● Decision-making: based on the results obtained, a user (or a machine) decides which actions to take (i.e., increase the humidity level in a greenhouse).
● Action: the performance of the needed action.
The cycle repeats itself consistently and allows farmers to always be aware of the state of their farm and immediately learn about any emergencies or issues. Now, let’s take a look at how the collected and analyzed data really helps farmers and where it can be used.
Top IoT use cases in Smart Farming:
We’ve talked a lot about sensors collecting the data and feeding them to the server so a user or a machine can take a certain action. But to better understand the importance of IoT in agritech, we’ll need to look at specific use cases.
Precision Farming:
Precision farming is defined as “a farming management strategy based on observing, measuring and responding to temporal and spatial variability to improve agricultural production sustainability”. In simple terms, precision farming implies customizing all processes for small areas within a field, instead of treating a field as a single unit. In this way, you provide precise treatment to a specific area, and it can be per square meter or even per plant or animal.
The main benefit of precision farming is that farmers can know exactly what area of the field demands fertilizers and pesticides (instead of applying them for the whole field). This approach allows not only saving costs but also reduces ecological footprint and improves the efficiency. Note that precision farming includes not only crop management, but livestock management as well.
Greenhouse Automation:
Climate control in a greenhouse is vital for effective crop management and production. But it usually takes too much time and effort to manually check the parameters (such as temperature or humidity) and then manually intervene to adjust them.
The use of IoT allows automating greenhouse management and, thus, greatly facilitating and optimizing the whole process. By placing various sensors in a greenhouse, you are able to 24/7 collect the needed information and immediately react to any alterations.
These two use cases above are considered the biggest – but IoT also helps with:
● Climate monitoring:
● Automated drone management;
● Predictive analytics (due to data collection).
As you can see, the main goal of using IoT in farming is collecting data to constantly monitor various conditions and environment and react accordingly. But in addition to IoT, there are many other technologies that the smart farming concept includes.
Smart Farming Technologies:
So, what else is agritech made of in addition to IoT systems? As we already mentioned above, there is a whole set of technologies that bring the smart farming concept to life. Let’s briefly take a look at each.
Drones:
The main purpose of drones in agriculture is remote field monitoring or, to be more specific, plant health monitoring. With the help of a drone, farmers can easily perform a visual inspection of the whole field in a few minutes and immediately identify whether all crops are healthy or not. Second, drones can help farmers spray fields with fertilizers, herbicides, pesticides, seeds, or whatever needed. In addition, drones are used for irrigation, field security, and even drone pollination – how cool does it sound?
To sum up, drones can serve either as a smart monitoring solution or as a robot that performs mundane tasks – you decide what area of application is the most suitable.
AI and Machine Learning:
Artificial Intelligence plays a big role in agriculture, just like in other industries. With the help of AI and machine learning, farmers can gather new insights quicker and easier, improve their monitoring and security processes, and overall increase productivity and efficiency.
You can use Machine Learning In Agriculture for:
● Predictive analytics and predictive maintenance (i.e., equipment monitoring);
● Livestock, poultry or aquaculture monitoring with the help of computer vision;
● Yield estimation;
● Smart Security Monitoring;
● Identification of degradation areas;
● Optimization of irrigation systems.
As you can see, the possibilities are really vast and impressive. You just need to form a request, and the ML engineering team will provide you with a solution.
Robotics:
Same as AI and machine learning, robots are widely used in farming and have become a valuable tech asset. Here are some most common applications:
● Harvesting and fruit handling;
● Spraying;
● Crop condition identification;
● Selective application of pesticides;
● Information collection.
The use of robots in farming greatly speeds up many processes and grants farmers an opportunity to focus on other critical tasks instead. And the best thing about it is that you can choose which tasks to automate, as RPA (aka robotic process automation) can be applied to almost everything.
Summary:
Smart farming is gaining traction as many industry experts see it as a way to battle hunger and provide the growing human population with enough food and supplies. There is still a long way to go before smart farming becomes widespread and adopted across the world, but it’s great to see more and more farmers slowly starting to digitize their processes.
Disclaimer:
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