What is agritech? Unlocking sustainability with connected farming

Have you ever wondered how the food on your table impacts our planet? The journey from farm to fork isn't just a matter of logistics – it involves critical issues like soil exhaustion and water consumption.

Shockingly, the agriculture and food industry are responsible for over 20% of global CO2 emissions. Apart from environmental damage, obsolete agricultural methods contribute to food insecurity and leave farmers 10-20 years behind competitors who have already adopted the new farming technology. 

Agricultural technology can be the way out – but only if used correctly. Curious about what "correctly" looks like? Let's explore the world of connected farming through real-world examples and see how it can revolutionize farmers’ approaches to agriculture.

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From Green Revolution to agritech: The evolution of farming

How did humanity come to the point where we can’t survive without technology? As you know, the sharp population growth started in the 21st century and paved the way for the farming revolution. Let’s take a small dive into history:

• The 1960s brought about The Green Revolution, which involved new plant breeding, irrigation, and management techniques that boosted crop yields and battled food scarcity.
• In the 1970s, herbicides were developed, and the first machinery for automated farming, such as the rotary combine, contributed to the industry's transformation. 
• The 1980s shined with the first genetically modified plant cell in 1982, and genetic engineering of crops with insect and disease resistance greatly decreased crop churn.
• In the 1990s, things were getting hotter. The rise of precision agriculture, GPS guidance, and satellite mapping started to shape the modern look of farming technology.
• The 2000s further accelerated this course, with agri-everything-tech becoming mobile, drones for watering and collecting plants, and real-time data monitoring of crops and farms down to the square meter.
• In the 2010s, agritech companies began to use big data analytics, digital platforms, and genomics to optimize operations.
• What about the 2020s? With the rise of AI, machine learning, IoT devices, and cloud computing, software companies have become reliable partners for farming businesses that want to optimize operations, resource allocation, and overall efficiency.

As you see, the evolution of agricultural technology is only natural. Just as the first farmers started to use a wheel or metal spade to improve their performance, you should consider implementing smart farming technologies.

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What is connected farming?

Simply put, connected farming uses innovative technologies to manage farms better – more cost-efficiently, more productively, and more sustainably. It gives business owners a complete picture of what is happening on their farms, optimizing operations and minimizing environmental damage and resource waste. 

The key components of connected farming technologies are IoT devices, sensors, and data intelligence software. Seamlessly integrated and connected, these agritech solutions collect, share, and analyze data in real time. How does this algorithm work?

IoT devices and sensors are deployed across the farm to monitor various aspects such as soil moisture, nutrient levels, weather conditions, crop growth, livestock health, and equipment performance. These devices continuously gather data and transmit it wirelessly to a central platform.

The data intelligence software then processes and analyzes this vast amount of information and notifies farmers about optimal times for planting, irrigation, fertilization, and harvesting based on real-time data analysis. With this data, farmers can apply them variably according to the specific needs of each section of the field.

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Connected farming explained: 4 layers of agricultural technology

To better understand farming connectivity, let’s view it as an interconnected flow that consists of 4 layers: 

• Perception layer 
• Connectivity layer
• Processing layer
• Application layer 

Each layer collects, transfers, and processes data to ultimately provide actionable insights for farmers. Here's how each layer contributes to the ecosystem:

Perception layer: IoT devices and sensors

This is where data collection happens. Sensors and IoT agriculture devices gather information on soil moisture, weather conditions, crop health, and more. These devices are the eyes and ears of the smart farm, providing real-time data from the field. This data is then transferred to dedicated cloud or on-premise servers, where it’s stored and analyzed.

Agrosmart is an agritech company that efficiently uses IoT devices to collect data from the fields, process it, and deliver actionable insights. By connecting to IoT sensors and satellite communication, Agrosmart saved farmers 60% of water and 40% of energy resources.

Connectivity layer: Networks

Once the data is collected, it needs to be transmitted. The connectivity layer ensures that all the information gathered by the sensors reaches the cloud or local servers. This can involve various communication technologies, ensuring seamless data flow.

There are several options for wireless IoT networks:

• Cellular networks are reliable solutions for global coverage and high bandwidth. NB-IoT is a low-power cellular network for a massive number of connections with small data packets, while LTE-M is a high-speed option for massive connections.
• LPWAN is a low-power wide-area networking technology for large-scale projects and a high density of connected devices, but the data transfer is limited.
• LAN/PAN, or simply, WiFi technology is suitable for short-range data-intensive applications in a small area. To this category, we can also refer the Bluetooth Low Energy (BLE), which is great for short-range communication with low power consumption.

These technologies consider factors like power consumption, range, and speed. IP networks use a lot of power and memory, while non-IP networks are more power-efficient.

Processing layer: Data storage and analysis

After the data is transmitted, it's processed and analyzed. A cloud platform aggregates the incoming data, storing and processing it for later use. It also performs initial tasks like data filtering, formatting, and cleansing. Once data is ready for analysis, algorithms come into play. 

Typically, custom-made AI and ML algorithms or off-the-shelf data intelligence solutions like Google Cloud IoT Core and AWS IoT analytics work on the data to derive meaningful insights. This layer is crucial for transforming raw data into actionable intelligence, predicting crop yields, or identifying potential issues before they become problems.

The analyzed data is presented to the users in reports and graphs. These reports connect the dots across agriculture workflows and provide forecasts or recommendations for improvement. For example, IBM’s iFarming visualizes the data from IoT sensors and processes it with AI to optimize irrigation. As a result, farmers reduce water use by 40% and increase productivity by 30%.

Application layer: End-user decision-making & automation

This is where the magic happens. Farmers access the processed data through user-friendly applications and dashboards. They receive recommendations and alerts that help them make informed decisions about irrigation, fertilization, pest control, and more. The application layer turns data into practical actions, driving efficiency and sustainability in farming operations.

Digital platforms like FieldView streamline data analysis and automate agritech operations based on where it’s better to focus your attention — reducing or increasing irrigation, changing the pesticides to less harmful chemicals, or applying crop cure methods if any disease occurs.

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Solving agricultural challenges with connected farming: Use cases

Connected technologies in agriculture hold immense potential to revolutionize farming practices and address challenges. The following use cases illustrate how connected farming solutions transform various aspects of crop cultivation and animal farming.

Crop cultivation

Over 70% of agribusinesses have reported that climate change is impacting their crop yields, with 36.7% noting that it makes yields highly unpredictable. The industry is sensitive to droughts and heavy rains, and lacks monitoring and warning systems to give adequate and timely responses to these events. 

With agricultural technology, farmers can predict extreme weather events and detect outbreaks of plant diseases early on, which allows them to respond on time and minimize the negative impact. 80% of agribusiness owners believe AI improves the accuracy of yield prediction and estimation. And agtech startups hold it true!

Benchmark Labs uses AI and ML to provide localized weather forecasts for farms. 1,500 machine learning models tailored to specific locations analyze data from on-site sensors and take into account microclimates and terrain differences. Optimized pest pressures and frost event management helped the company to increase yield by 50-100% and reduce water usage by 10%.

Another agtech startup, FarmSense, won a grant to create a digital mosquito surveillance platform. The technology uses computational entomology, artificial intelligence, and machine learning to reduce mosquito-borne diseases and improve pest management. Currently, the company has installed around 500,000 data points and expects to improve crop health globally with micronutrient enhancement.

Animal farming

Animal farming faces a web of challenges. Livestock is susceptible to diseases that spread quickly in dense populations. Extreme weather events disrupt feed production and animal health. Additionally, traditional methods lack real-time data on animal health and resource utilization, making it difficult to optimize feeding and ensure welfare.

Connected farming technologies provide solutions for monitoring animal health, tracking herd locations, and optimizing breeding programs:

• Wearable biometric sensors and camera systems with AI analytics detect early signs of illness before symptoms become severe. For example, Cainthus uses sensors and computer vision to identify visual and behavioral indicators of disease in dairy cows.‍
• GPS trackers, sensor networks, and RFID tags allow farmers to monitor cattle's real-time locations. Vence Virtual Hencing provides herd-tracking solutions using GPS tags and wireless nodes to prevent livestock loss or theft.‍
• Breeding management solutions like the HerdX platform track cow heat cycles and recommend timing for artificial insemination. And sensor-integrated milking systems like DairyMilk M6800 from GEA follow each cow's needs and milk production to give customized feed rations.‍
• In China's Connected Cow project, farmers managed to achieve a 50% annual income from dairy cows by using agritech technology to monitor every cow’s health and track its movement if it strayed.

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How smart agricultural technology tackles food insecurity

In 2023, 281.6 million people across 59 territories faced acute food insecurity, and unsustainable farming is a big part of the problem. With the global population reaching 10 billion by 2050 — 2 billion higher than today — the pressure on food demand is inevitable. 

We asked ourselves how farmers will feed our planet's growing population. The answer lies in the integration of agricultural technologies. By adopting precision farming, smart irrigation systems, and advanced crop monitoring techniques, farmers can boost yields, reduce waste, and ensure sustainable food production.  

Experts say the global adoption of agritech can improve farm productivity by 70% by 2050. This surge in productivity will be driven by the widespread use of data analytics, IoT devices, and automated machinery. These technologies allow farmers to optimize every aspect of their operations, from planting to harvesting, ensuring that resources are used effectively: 

• Satellite imagery, drones, and soil sensors provide real-time data on crop health, soil conditions, and weather patterns. This helps farmers make informed decisions about planting, irrigation, and harvesting to minimize waste and maximize yield. Satellite imagery has already reduced fertilizer use by 20%.‍
• Smart irrigation systems use sensors and automated controls to deliver the right amount of water to crops at the right time, reducing water usage and preventing over-irrigation.‍
• Hydroponic systems save up to 90% of the water used by traditional soil farming.‍
• Advanced crop monitoring techniques help detect pest infestations and disease outbreaks early, allowing for targeted interventions that reduce the need for chemical pesticides and herbicides. This not only protects the environment but also ensures that crops remain healthy and productive.

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Sustainability in agribusiness: Combating climate change with agtech

Traditional farming has been exhausting natural resources for centuries, and it’s up to our generation to change that. Specialty crops agribusinesses pioneer sustainability initiatives that benefit both people and the planet:

• 77% of these companies have already implemented one or more sustainability programs 
• 40% embed sustainability into their core corporate values 
• 80% believe their efforts are hitting the mark

Agritech software development is what helps agribusiness not just adapt to climate change but actively fight it, paving the way for a greener, more sustainable future. We want to share our client’s case of how connected farming transformed traditional farming operations into a future-proof, technological, and sustainable business.

A greenhouse business struggled to manage vast amounts of data across its areas and analyze multiple aspects, such as crop yields, environmental conditions, resource allocation, and finances. Another typical traditional way of farming was managing the data with outdated paper records and spreadsheets. Given that the greenhouse was located in a remote and quite distant location, tracking key performance indicators off-site was close to impossible, and owners had to visit the greenhouse personally to make informed decisions. 

By partnering with COAX, the greenhouse embraced a comprehensive digital transformation with a connected farming solution tailored to their needs. This involved integrating IoT devices for data collection, a low-power wide-area network for connectivity, cloud-based data processing, and a custom web application. 

The platform gathered real-time data on crop stages, environmental conditions, resource consumption, financial management, workforce performance, and customer/supplier relationships. It facilitated 100% operational transparency, enabling data-driven decision-making and remote management capabilities.

By precisely determining their product strategy and vision, we developed an efficient connected farming solution to integrate various business functions, from production analytics to financial management, and bring tangible results.

As a result, our clients increased revenue by 14%, harvested 15% more yield, and spent 12% less on operational costs. Smart farming technologies helped our clients build a sustainable farming business, cutting resource waste by 25%. 

This is only the beginning: the agritech company launched an "open greenhouse" initiative. Agrotourism is gaining traction as people are eager to understand sustainable farming practices and witness farming innovations in action. This immersive experience not only educates visitors but also fosters a deeper connection between consumers and the source of their food. 

At COAX, we take social responsibility seriously, and these steps to the future of farming are as valuable for us as for our clients.

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FAQ

What is connected farming?

Connected farming uses innovative farming technology like IoT devices, sensors, and data analytics to manage farms more efficiently, reduce waste and environmental damage, and optimize operations.

What are the benefits of connected farming?

Benefits include increased crop yields, reduced water/fertilizer usage, early detection of crop diseases, improved livestock management, lower operational costs, and enabling more sustainable practices.

How does connected farming compare to traditional farming methods?

Traditional farming often relies on outdated practices, while connected farming leverages modern agritech for real-time monitoring, data-driven decisions, reduced waste, and automation.

How is agricultural technology helping address global food insecurity?

By enabling more efficient and sustainable farming practices, agricultural technology can help increase food production to feed the growing global population while reducing environmental impact.

What role do AI and machine learning play in connected farming?

AI and machine learning algorithms can analyze the data collected from IoT sensors to provide predictive insights, optimize processes like irrigation, and enable precision agriculture.