Smart farming: agricultural technology of the future

Like manufacturing, agriculture is undergoing a transformation known as the Third Green Revolution. After two previous major leaps, caused by novel plant breeding techniques and advances in genetics, the driving force behind changes now is data science. These changes are also accelerated by the pressing global need for food. Like a smart factory, a smart farm focuses on optimizing work processes using the latest Information and Communication Technologies, including hardware, sensors and robots, and software solutions. And they indeed can improve every facet of farming operation, with excellent results like increasing resource efficiency, e.g., water usage, higher food safety and reduced pesticides.

Most technologies, like agricultural robots, are still not affordable to small farmers or are at the prototype stage. And it might take a long time until they become mainstream, especially in developing countries.

According to Statista, the smart farming market will grow to 23.14 billion U.S. dollars by 2022. The digital overhaul will allow farmers to remain competitive and sustainable and contribute to climate change prevention.

Benefits of smart farming

• Process automation
• More controllable processes thanks to constant data collection and analytics.
• More accurate yield forecasts
• Improved distribution planning
• Risk management
• Enhanced product quality and quantity
• Higher revenues

Let us have a closer look at these agricultural technologies of the future.

Internet of Things

An average farm can potentially generate millions of data points weekly through a system of sensors. The Internet of Things creates a possibility for a farmer to get meaningful insights from this data, which simplifies strategic decisions, and control processes from a smartphone.

How it works:

• Observation. Sensors gather data from plants, animals, soil, or the environment.
• Analysis. The data is processed at a cloud-based IoT platform: the system compares the values to predefined “perfect” settings – business logic – and identifies any deviations.
• Decision. If an abnormality of a bottleneck is detected, a human or Artificial Intelligence decides how to eliminate it.
• End of cycle. After the action is taken, the cycle repeats. 24/7 monitoring of livestock and crops allows prevention of issues and timely reaction before they aggravate.

Types of sensors:

• Smart cameras – used for weeds detection and precision fertilizing
• Location – establish a connection with GPS satellites and serve for land mapping
• Airflow – identify soil air permeability
• Optical – measure soil parameters, e.g., moisture
• Electromechanical – identify soil composition and deficiencies by measuring specific ion levels

Smart greenhouses

The amount of manual labor is also drastically decreased at greenhouses, which are a vast farming trend for the years to come. Automatic climate control through IoT sensors increases productivity and prevents energy loss. Environmental parameters optimal for each crop type are stored in the cloud and maintained by the system without very little manual intervention. Automated self-regulating greenhouses with weather stations help to achieve maximum crop productivity.

Advantages of a smart greenhouse:

• Optimum plant growing conditions with minimum energy consumption.
• Precise irrigation and cultivation.
• Easy infection and disease control.
• High security and theft prevention

Agricultural robots

Agricultural robotics is a trendy, fast-paced, and promising scientific area. Now expensive and flawed, ag-bots will become farmers’ best assistants shortly. They have a wide range of applications, from mowing, thinning, seeding crops to herding, milking, and washing cattle.

Crop harvesting

Robots are perfect for replacing humans with monotonous and labor-intensive tasks. However, it is not easy for machines to achieve manual dexterity to pick some fragile fruit and vegetables. A vivid example of success is “Vegebot,” designed at Cambridge University. The prototype uses computer vision to achieve accuracy so amazing that it can harvest delicate lettuce leaves. Moreover, thanks to a machine-learning algorithm, it detects if the fruit is ripe enough. The improvement still to be made is the human-like speed of work.

Weeding

Weeds can be incredibly resilient and hard to eradicate. It seems mission impossible with manual work and not eco-friendly considering pesticide usage. For this purpose, Canadian company Nexus Robotics has developed a fully autonomous robot prototype, “La Chevre.” With the help of cameras and neural networks, it can distinguish valuable plants at all growth stages from weeds and remove them neatly. It can operate round the clock and collect data on soil and environmental conditions in different areas for better farming decisions in the future.

Electric autonomous tractors and their potential in agriculture

Electric autonomous tractors represent a significant advancement in agricultural technology. These tractors combine electric vehicle (EV) technology with autonomous driving capabilities, offering numerous benefits to modern farming practices. For instance, the Monarch Tractor’s MK-V model can perform various tasks such as seeding, weeding, and harvesting with minimal human intervention. These tractors help reduce carbon emissions, lower operational costs, and increase efficiency by operating continuously without the need for breaks. The integration of AI and machine learning allows these tractors to optimize field operations, making precise adjustments based on real-time data.

Seeding and weeding robots

Seeding and weeding robots are transforming modern agriculture by automating labor-intensive tasks. Naio Technologies’ Dino is a prime example of a weeding robot that uses advanced sensors and AI to navigate fields and remove weeds without damaging crops. These robots help reduce the reliance on chemical herbicides, promoting more sustainable farming practices. Additionally, seeding robots, such as those developed by ESCATEC, offer precision planting capabilities, ensuring optimal seed placement and spacing. These technologies not only improve crop yields but also reduce labor costs and increase overall farm efficiency.

Automated irrigation systems

Automated irrigation systems are essential for optimizing water usage in agriculture. These systems use a combination of sensors, smart controllers, and distribution networks to monitor soil moisture levels and deliver water precisely when and where it is needed. For example, the RAPID system integrates real-time data from soil moisture sensors and weather forecasts to adjust irrigation schedules automatically. This approach helps conserve water, reduce waste, and improve crop health by ensuring that plants receive the right amount of water at the right time. Automated irrigation systems are a crucial component of smart farming, contributing to more sustainable and efficient agricultural practices.

Robotic farms

99% autonomous, with humans only as supervisors, robotic farms look very futuristic. Bowery Farming company uses Artificial Intelligence with other advanced technologies to achieve a hundredfold increase in efficiency compared to outdoor farming. The company developed an operating system – The BoweryOS that tends to the needs of each plant – gives a plant more light or nutrients or identifies perfect harvesting time. Thanks to machine learning, the system performs the interpretation of massive amounts of real-time data, collected by cameras and sensors, and improves its analytical performance with each cycle.

Agricultural drones

Agricultural drones or UAVs perform a variety of tasks, from spraying to crop monitoring and soil analysis. For instance, drone fertilizer spraying is up to 60 times more effective than manual. In addition, aerial drones collect thermal and visual images of fields that help farmers diagnose crop and soil health.

Regenerative agriculture: the future of farming

The global need for food is growing as well as population incomes, especially in the developed countries. Health-conscious people tend towards protein-rich plants like legumes and organic produce. At the same time, traditional farming and deforestation associated with it already have disastrous consequences for the environment. The innovative technologies empower farmers not only to survive and remain profitable but join the combat climate change. Regenerative agriculture includes techniques like cover cropping and conservation tillage that help decrease carbon emissions into the atmosphere and alleviate the climate impact. Data analytics tools facilitate the adoption of the regenerative approach and help to decarbonize the agricultural supply chain footprint. To have a future, agricultural entrepreneurs must adopt innovation and keep the planet’s health in mind.

Interoperability challenges in smart farming

Interoperability is a significant challenge in the adoption of smart farming technologies. The integration of various devices, platforms, and systems often leads to compatibility issues, hindering seamless data exchange and operational efficiency. For instance, different manufacturers may use proprietary communication protocols, making it difficult for equipment from different brands to work together. This lack of standardization can result in fragmented data, complicating the decision-making process for farmers. Addressing these interoperability issues requires the development of universal standards and protocols that ensure compatibility across different technologies. Collaborative efforts among technology developers, industry stakeholders, and regulatory bodies are essential to create an interoperable ecosystem that maximizes the benefits of smart farming.

Future prospects and global trends impacting agriculture

The future of agriculture is being shaped by several global trends, including climate change and demographic shifts. Climate change poses a significant threat to agricultural productivity, with increasing temperatures, changing precipitation patterns, and more frequent extreme weather events affecting crop yields and livestock health. To mitigate these impacts, farmers are adopting climate-smart practices and technologies that enhance resilience and sustainability. Additionally, demographic shifts, such as urbanization and population growth, are driving changes in food demand and consumption patterns. As urban populations grow, there is an increasing need for efficient and sustainable food production systems to ensure food security. These trends highlight the importance of innovation and adaptation in agriculture to meet future challenges and opportunities.

Role of government and industry collaboration in overcoming smart farming challenges

Collaboration between governments, industry, and other stakeholders is crucial for addressing the challenges in smart farming. Governments play a vital role in creating supportive policies, providing funding for research and development, and facilitating knowledge exchange. For example, initiatives like the Agriculture Improvement Act in the United States support the adoption of smart farming technologies through financial incentives and research grants. Industry collaboration is also essential, as it fosters innovation and the development of scalable solutions. Public-private partnerships can drive advancements in technology, improve infrastructure, and enhance the overall efficiency of agricultural practices. By working together, governments and industry can overcome barriers to smart farming and promote sustainable agricultural development.

The Blackthorn Vision team has built many successful solutions for leading companies. We have expertise in data analytics, AI, and Machine Learning to build game-changing software tailored for your agricultural business. The holistic approach means you get a full spectrum of digital services from consulting to ready product maintenance and support. The easiest way to get started is the Discovery Phase that will visualize your idea within a few weeks. Let’s partner up and digitize your farm operations for a productive future.