Countries all over the world are exploring innovative ways to make agriculture more sustainable as the world’s population continues to rise and climate change exert growing strain on food production. By 2050, the world’s population is predicted to be roughly 10 billion people while farmers continue to confront more pest outbreaks, unpredictable weather and declining agricultural resources.

In the face of these issues, institutions and governments are turning more and more to “smart farming” technologies – digital systems that help farmers monitor crops, identify illnesses early, decrease waste, and make better decisions.

A group of researchers, Joli Dutta, Jumi Dutta, and Sukanya Gogoi studied the use of technologies for smart farming in monitoring and detection of crop pests and illnesses, especially in developing nations such as India. Smart farming is defined in the study as the employment of Information and Communication Technologies (ICTs) in agriculture. These technologies include drones, sensors, Geographic Information Systems (GIS), Artificial Intelligence (AI), mobile applications, robotics, and Internet of Things (IoT) devices used to collect and analyze farming data in real time.

READ: Smart farming: An opportunity for efficient monitoring and detection of pests and diseases

According to the study, these technologies can help farmers apply the right quantity of water, fertilizer and pesticides at the right time, avoiding unnecessary costs while enhancing crop output.

One of the primary findings of the study is the increasing threat of pests and diseases to crops. Many farming areas find that farmers only discover infestations after crops have been badly damaged. If it is not detected in time, this can result in major crop losses, reduced farmer income and increased food poverty.

The technologies of smart farming strive to solve this problem by monitoring earlier and sharing information faster.

For example, camera and sensor drones can scan broad agricultural areas and detect damaged crops by detecting changes in plant color and temperature. Stressed or diseased plants reflect light differently, allowing drones and imaging systems to detect potential outbreaks before they are evident to the human eye, the study says.

The research also describes how agricultural specialists use GIS and remote sensing technologies to monitor disease outbreaks and locate infestation “hot spots.” Remote sensing is the process of acquiring information about land and crops without being physically there, usually by satellites or from the air.

The convergence of these technologies will allow specialists to track insect movement across extensive agricultural regions and respond more rapidly to looming agricultural concerns.

Another important part of smart farming is the Internet of Things (IoT), a framework where connected devices constantly collect and share data over the internet. In farming, IoT sensors can monitor the moisture, temperature, humidity, rainfall and conditions of plants in the soil in real-time.

The paper mentions certain digital agricultural methods that are already in use in India and other countries. One example is Plantix, a mobile app that uses artificial intelligence to diagnose plant diseases, pest damage and nutritional deficiencies from images uploaded by users. A second technology, called Trapview, automatically tracks insect populations by employing smart traps that send photographs of pests in real time to experts for examination. Meanwhile, the e-SAP platform developed in India lets farmers, agricultural workers, scientists and policy officials communicate pest surveillance information more rapidly via ICT-based monitoring devices.

The research also mentions government-supported agricultural apps such as Kisan Suvidha and Pusa Krishi, which provide weather forecasts, crop advice, market prices and pest management information to farmers via mobile devices.

Researchers say these technologies can help farmers to reduce unnecessary application of pesticides by allowing them to administer chemicals just when and where they are needed. More effective pest identification could potentially cut farming expenses, minimize environmental harm, and enhance public health consequences from overuse of pesticides.

On the other hand, while digital agriculture can increase efficiency and productivity, many developing countries still face challenges such as lack of good internet connectivity, expensive technology, and lack of training for farmers. Small-scale farmers may not have the money to buy drones, sensors, automated systems or advanced digital equipment.

The survey also highlights the fact that many farmers are still not aware and technically knowledgeable in new agricultural technologies. Yet, if digital systems are not supported well, they may be out of reach of the same populations they are supposed to serve.

Researchers have also cautioned against unequal access to technology as this might increase the existing disparities between large commercial farms and smallholder farmers. If smart farming projects are focused exclusively on capital intensive agricultural sectors, then smaller rural communities are at risk of being left behind in the process of agricultural modernization.

The study shows that the introduction of new technologies alone is not sufficient for the success of smart farming. It also depends on governance structures, farmer education, institutional support and inclusive communication methods that ensure that the farmers can engage in meaningful technological progress.

Key policy recommendations:

Scaling up farmer training and agricultural extension services: Continuous training for farmers on digital agriculture tools, pest monitoring systems, drone technology and precision farming practices is essential.

Financial support for smallholder farmers: Governments and financial institutions should put in place subsidy schemes, cheap lending facilities and technology transfer programmes that enable smallholder farmers to acquire smart farming technologies without the heavy financial burden.

Strengthening governance and cybersecurity of agricultural data: As data becomes more critical in agriculture, governments must establish policies to protect agricultural data privacy, foster transparency, and secure the integrity of information systems.

Contributor: Eduardo Salvador, ComDev Asia intern