Artificial Intelligence (AI) For Agricultural Advancement

In today’s world, Artificial Intelligence (AI) is changing how we farm. It’s turning agriculture from an old-fashioned field into a high-tech industry. Farmers used to rely on hard work and good weather, but now they’re using AI to boost their output and work smarter. This shift to AI in farming isn’t just a cool new thing – it’s become a must-have. It’s changing the whole game, from how we deal with farming problems to how we spot new chances. AI has an impact on farming at its core leading to smarter and more effective ways of doing things. Experts think there will be about 10 billion people on Earth by 2050. This means we’ll need to grow 50% more food than we did in 2013 even if the economy doesn’t grow much. Right now, we use about 37.7% of the Earth’s land to grow crops. Farming plays a big part in making rich countries richer and helps poorer countries’ economies too. As farming has grown, country folk have seen their earnings go up a lot. So, it makes sense to focus more on farming.

The AI in agriculture market is expected to grow from USD 1.7 billion in 2023 to USD 4.7 billion by 2028, according to Markets and Markets.

The agricultural sector faces huge pressure to boost crop production and yields worldwide. Two main strategies have emerged to tackle potential food shortages: expanding farmland and adopting large-scale farming, or using new practices and tech to increase output on existing land. Many obstacles stand in the way of desired farm productivity, including small land holdings, worker shortages, changing climate environmental concerns, and declining soil health. These challenges are pushing modern farming to branch out in new directions. Farming has progressed a lot since the days of hand plows and horse-drawn tools. Each growing season brings new tech to boost efficiency and get more from the harvest. However, many farmers and big agri-companies often overlook the benefits AI can bring to their operations. Still, fresh ideas keep popping up in every field, and farming is no different. AI offers solutions to many problems and helps reduce the drawbacks of old-school farming methods.

Data-based decisions: Precision and Efficiency

Data drives the modern world. Farms use data to gain deep insights into every farming step. They track each acre, watch the whole supply chain, and study how crops grow. AI prediction tools are changing agri-business. These tools use data from many sources, like space photos and ground sensors. AI then gives farmers detailed information about their fields. This data-based approach helps farmers use water, fertilizers, and bug sprays more. This knowledge helps farmers protect their harvests before problems start. AI lets farmers collect and process more data faster. It also looks at what people want to buy, predicts prices, and finds the best times to plant and pick crops.

Pest Detection and Crop Health Monitoring

Traditionally, pest control in agriculture has relied heavily on continuous pesticide applications. While this approach on the one hand is effective in combating pests, on the other hand, it often leads to overdose, posing a threat to environmental health and human safety solutions. AI in agriculture uses advanced techniques such as analysis of satellite-captured thermal imagery. This new method can quickly detect potential pest outbreaks or crop-affecting diseases. By analyzing subtle changes in temperature and other signals in these images, AI systems can pinpoint areas of concern long before visible signs of infection or disease appear. This ability to see quickly is critical; it empowers farmers to adopt a targeted approach in dealing with crop issues. Reduced chemical use means that less of the water flowing into adjacent water bodies is at less risk of affecting non-target species including beneficial insects and local fauna.

Automation impact

Farming is hard, so labor shortages are nothing new. Thankfully, automation provides a solution that doesn’t require hiring a lot of people. When the machine was emphasized and agricultural work was only a few hours away, the new wave of the digital wave materialized again, the driver, smart irrigation, Internet of Things (IoT), agricultural software, fruit Automated farm machinery such as greenhouse robots AI-powered harvesters are just some examples Compared to any human farmer for employees, AI-powered machines are far more efficient and accurate. Coupled with IoT sensors that monitor soil moisture levels and weather conditions, algorithms can decide how much water to supply crops in smart greenhouses in real-time AI automatically adjusts depending on temperature, humidity, and light levels real-time information to improve plant growth.

Detecting leaks or damage to irrigation systems

AI plays an important role in detecting leaks in irrigation systems. By analyzing the data, algorithms can identify patterns and anomalies that indicate a possible leak. A Machine Learning (ML) model can be trained to recognize specific signals of leakage, such as changes in flow or pressure. Real-time monitoring and analysis provide early detection, preventing water wastage, including potential crop failure. AI also incorporates weather data into crop water demands to pinpoint areas of overuse. By detecting leaks and providing alerts, AI technology increases water use efficiency to help farmers save resources.

Crop and Soil monitoring

Soil nutrient balance can have a significant impact on the growth and quality of crops. AI helps farmers to identify these nutrients and their impact on crop production and make the necessary adjustments without any problem. Computer vision models can track soil conditions to gather the necessary data to prevent crop diseases and use plant information to determine crop health, flag specific cases, and make crop forecasts. Wheat growth and tomato ripening are just some of the things humans cannot do.

Monitoring livestock health

Identifying health issues in animals may seem easier than detecting them in crops, but it’s actually quite challenging. AI can be used for farming through the Cattle Eye application uses drones, cameras, and computer vision to remotely monitor livestock health, and find out what’s going on with them, births, etc. Cattleeye analyzes feed additives for AI and ML solutions to get a better idea of the environmental impact. Farmers can use this knowledge to improve animal welfare and milk output.

Surveillance

Farm management involves the maintenance of security. Burglars are a common sight on farms, it’s impossible to watch every field. Animals can also be a threat like foxes in chicken coops or farmers’ own livestock damaging crops or machinery. Computer vision machine learning video surveillance systems could detect security breaches in seconds. Some technology is mature enough to protect their staff from unlicensed visitors.

Impact on Small-Scale Farmers and Local Communities

AI provides a wealth of information and tools that help local farmers make informed decisions about farming practices. The focus is on selecting the most suitable time for planting, ensuring proper soil quality, utilizing appropriate water sources, and implementing pest management strategies. Farmers can optimize yield and resource utilization, and increase crop productivity and income by using data-driven AI tools. Hence, these developments are bringing about change, especially in areas where agriculture is the primary source of income and economy. Enhanced efficiency and productivity benefits for farmers not only improve their income but also contribute to economic growth and stability within their communities. Small farms can become more competitive in the open market by utilizing AI-equipped tools, breaking the cycle of dependence on outdated farming methods and limited resources. Agriculture is a whole lot more affluent, people are more empowered, and smart data-driven farming promotes fairness and success, not scale.

The Future of AI Farming in Pakistan

Pakistan, a country with deep agricultural roots, relies heavily on farming. Agriculture makes up about 24% of the country’s GDP, with Pakistan being a leading producer of wheat, cotton, sugarcane, mangoes, dates, rice, and oranges. As the world faces growing challenges in food production, technology-based farming techniques are emerging as a game-changer for Pakistan’s agriculture, paving the way for more sustainable and resilient farming practices. Recognizing the potential of smart farming, Pakistan launched the Land Information and Management System (LIMS) under the Green Pakistan Initiative (GPI), a key project of the Special Investment Facilitation Council (SIFC). This system uses cutting-edge technology to promote precision agriculture, providing farmers with real-time data on climate, crop conditions, water management, and fertilizer use. With this information, farmers can make smarter decisions, leading to better crop yields and more efficient use of resources.

Imagine a future where tractors drive themselves, planting, harvesting, and weeding with incredible precision, or where irrigation systems know exactly how much water your crops need and deliver it perfectly every time. This isn’t just a dream—it’s what the LIMS is working to make a reality. Currently, LIMS is in the Research and Development (R&D) phase, testing these smart agricultural practices on model farms in Punjab through the FonGrow initiative. But the innovation doesn’t stop there. The GPI is also transforming livestock farming with the Green Corporate and Livestock Initiative (GCLI). By using AI-driven techniques like artificial insemination, the potential to increase livestock production is staggering from just 40-50 births per male animal each year to nearly 5,000. And the benefits of AI in agriculture are far-reaching. It’s not just about improving efficiency. AI is helping to develop crop varieties that can endure extreme weather and resist diseases, significantly reducing the environmental impact of farming. Most importantly, it’s playing a vital role in securing food supplies for future generations.

LIMS, by harnessing advanced technology, is not only boosting agricultural production but also helping Pakistan reduce its reliance on imports and increase its exports. And there are signs that these efforts are paying off. In 2023-24, Pakistan’s agricultural exports reached $5.2 billion, a 13% increase from the previous year. This growth, driven by better productivity, prices, and global demand, includes major exports like rice, fruits, vegetables, cotton yarn, and fish. The shift from manual labor to planning and supervising AI-driven farming systems is not just a change in how farming is done—it’s a transformation of the entire agricultural landscape. As AI technology continues to evolve, it holds the promise of turning agriculture into a more productive, sustainable, and equitable industry, meeting the challenges of the 21st century head-on.

Challenges for AI agriculture in Pakistan

AI is a concept that is only relevant to the digital world, with no connection to farming. Usually, it’s because you don’t know AI tools. AI in biotechnology is slow to be adopted in agriculture because there is no understanding in many areas, especially in nontechnical fields. The government must make significant efforts to help people understand the application of AI in agriculture. AI is a good investment for every farmer, it can help to sustain a farming industry. Still, some issues need to be addressed.

Large upfront costs

AI solutions are relatively cheap in the medium to long term, but the initial investment is not without consequences. AI is not a viable option for the moment, especially for small farmers because of the financial difficulties of many farms and agri-businesses. AI farms cost less but technology improves it. Businesses can get government grants and private investment.

Reluctance to embrace new technologies and processes

AI is a great way to help farmers, but people don’t know how to embrace it. Resistance to innovation and a reluctance to risk new processes are the main obstacles to farming and its profitability. Farmers need to know that AI is just a refined version of simpler field data processing techniques. The public and private sectors must provide incentives, resources, and training to encourage agricultural workers to adopt AI. The governments must also create regulations to ensure that workers are exposed to the technology.

Lengthy technology adoption process

Lack of infrastructure for AI is a common issue in the agricultural sector, along with a lack of knowledge and experience. Farms that have the technology already have the potential to make significant strides, but they may still face obstacles. Infrastructure challenges are also faced by agri-tech providers and software companies. A good way to do this is to approach farmers step by step, by using simple technology, like an agricultural trading platform. Once farmers get used to a simpler solution, providers can add additional tools and features to AI-based farms.

Technological limitations

AI is still a concept, but it has limitations. Accurate models require diverse, high-quality data, which can be difficult to get in agriculture. Robots with sensors can help you to adjust to changing farming conditions. The challenge is to keep up with the research and data analysis. Farmers need to prioritize their decision-making over leaving it to AI. Early stages of AI adoption may benefit from manual monitoring.

However, Pakistan’s journey toward AI-driven farming isn’t without its challenges. For many farmers, who have relied on traditional methods for generations, embracing new technology can be daunting. Plus, small farmers often don’t have the tools or resources needed to make the most of these advancements. To truly make this transition successful, both the government and private sector companies need to step up—offering loans, building infrastructure, and creating awareness programs that support farmers in adopting smart agriculture. By working together, we can help ensure that every farmer has the opportunity to thrive in this new era of farming.

References

1. https://intellias.com/artificial-intelligence-in-agriculture/
2. https://www.linkedin.com/pulse/how-ai-driving-agricultural-innovation-ronald-van-loon-jb27e/
3. https://www.sciencedirect.com/science/article/pii/S258972172030012X
4. https://www.dawn.com/news/1807519
5. https://www.sciencedirect.com/science/article/pii/S2772375524000364

 

(The Writer is an accomplished Electrical Electronics Engineer specializing in the innovative field of IoT-driven smart devices. Experience in designing and implementing IoT solutions that enhance efficiency, connectivity, and user experience across various industries. Email: [email protected])