Digital Agriculture vs. Traditional Farming: Do You Need to Evolve?

Digital Agriculture vs. Traditional Farming: Do You Need to Evolve?

Most industries rely on data to stay competitive, and this requires a digital transformation. For the agriculture industry, switching to smart digital farming also means better productivity, resource consumption optimization, accurate predictions, better decisions, fewer risks, the reduction of routine tasks, and a better opportunity to solve the global problem of food shortage.

Considering these benefits, is digital agriculture the future of the industry? The field of agriculture robotics is expected to reach $75 billion in revenue by 2024, and this is not the only example of digital technology in agriculture that will drive this industry towards progress and innovation. Let's find out how digital agriculture solves more problems than traditional agriculture practices.

Traditional and Digital Agriculture Pain Points and Challenges

The agricultural industry is pretty complex. That is why this industry has challenges and pain points. Fortunately, most of them can be solved with the help of digital farming technology. To better understand its use cases and the benefits of digitization of agriculture can promise to a farming business, let’s get started by reviewing the core problems this industry faces.

  • Weather. Harvesting success has always been dependent on the weather. A good harvest requires a balance of rainy and sunny days, comfortable temperatures, and the avoidance of weather-related disasters. Farmers have traditionally predicted the weather guided by their experience and the signs of nature.
  • Aging workforce. Farming is not a career path that many young people pursue. Instead, they choose more promising occupations. This, in turn, leads to an aging agriculture workforce and productivity loss.
  • Unpredictability. The actual amount of food harvested is challenging to predict because it depends on many external factors. Digital agriculture solutions come with historical data analysis and predictive features that may provide farmers with a clear picture of what to expect.
  • Routine and time-consuming tasks. Many of the processes in agriculture are regular and manual. The use of machinery and equipment doesn’t cut down much on manual labor, which can be cheap but difficult to find for this industry.
  • Lack of water. There can be no harvest without water, but due to a global shortage because of climate changes, agricultural businesses either pay more to access it or consume less water and get a smaller harvest as a result.
  • Global hunger. 10% of the global population still suffers from starvation even though the agricultural industry produces enough food to feed every person on the planet. Still, one-third of the food produced is wasted mainly because of unconscious shopping and supply chain loopholes.

Core Technologies Behind Digital Agriculture

What technologies do digital agriculture companies use to solve the challenges it faces? Below are the core innovations that drive digitalization in agriculture and provide an opportunity to become more productive, optimized and ecology-focused.

  • Global Positioning System (GPS). While GPS tracking isn’t a new technology, it is successfully used as a part of digital agriculture technology. E.g., by powering drones for livestock location tracking and fleet management.
  • Machine learning (ML). Machine learning is at the heart of digital agriculture. Its ability to gather and analyze data in real-time and make smart predictions and suggestions is the key to farmers making more beneficial decisions that lead to better harvests and lower operational costs. Technologies, such as face and image recognition and computer vision power robotic solutions, are also used in agriculture.
  • Internet of Things (IoT). IoT devices such as robots work in conjunction with machine learning to gather data, transfer it to a farmer’s mobile device and enable him or her to make a data-driven decision.
  • Self-driving technologies. Stock tracking drones are powered by GPS, M. They are one more example of the Internet of Things for digital farming.
  • Robotic Process Automation (RPA). RPA is an approach to automating routine tasks like getting rid of weeds. In this case, a smart farming system is also powered by a mix of ML, computer vision and IoT.

Innovation in Digital Agriculture: Use Cases and Examples

A digital farming system is often a mix of the technologies we talked about. Below are the benefits and opportunities agriculture digitalization can promise for businesses in this industry.

  • Better weather prediction. The IBM Watson Platform utilizes weather data analytics to build decision-making models for farmers based on weather data, harvest specifics, and the current health of the crop. It is an example of digital agriculture powered by AI.
  • Smart water and pesticide consumption. One of the goals of digitization in agriculture is to help farming businesses effectively use their resources. For example, advanced solutions can calculate the amount of water and pesticide needed to successfully grow a particular plant, taking into account soil and weather conditions so the farmer can make informed decisions about what to grow based on the resources available.
  • Careful crop planting. Each crop needs to be planted at a particular depth. Automated robots can calculate the depth, and also plant it using a robotic process, automation, sensors and computer vision.
  • Automatic weed control. Robots equipped with computer vision can distinguish useful plants from weeds and carefully remove the latter, sparing the farmer from getting involved in that manual job. Take a look at Tertill to find out how this digitalization in agriculture works in a vegetable garden.
  • Automated pruning and harvesting. There are robots for weed removal and planting with solutions to prune plants and help gather the harvest. For example, there is a solution for automated strawberry picking.
  • Livestock tracking and management. Drones are the primary tools that assist with this. Agriculture is expected to be the top target market for drone development, reaching $420 million by 2028. Drones can be used for real-time data collection on the health of crops, livestock location tracking and theft prevention.
  • Streamlined sales of farming products. Indigo Ag is a marketplace that connects farmers and buyers to help them make better deals and prevent overproduction, for example.
  • Supply chain optimization. Digital farming solutions can help with the problem of food waste by optimizing agriculture supply chains.

Conclusion

Digital farming companies supply farmers with high-end solutions for their business needs. Not all of them are perfectly tailored to the challenges your farming enterprise faces, though. Custom agriculture software development can be a winning idea to get started with the digitalization of agriculture within your farming business.

Cprime Studios has in-depth experience in agtech solutions creation, so get in touch with us for a free consultation and practice-proven insights!