The Importance of IoT in Agriculture
As the global population is projected to reach 9.8 billion by 2050 (United Nations, 2019), the demand for food is expected to surge dramatically. Traditional farming methods are increasingly insufficient to meet this demand. The Internet of Things (IoT) offers transformative potential by enabling real-time monitoring, data-driven decision-making, and automation in agriculture.
Why IoT Matters
IoT matters because it revolutionizes agriculture by enabling real-time data collection and automation, resulting in increased crop yields, improved resource efficiency, and more sustainable practices. It helps farmers make informed decisions, reduce waste, and respond swiftly to environmental challenges. As global food demand rises, IoT's ability to optimize farming processes is vital for ensuring food security, environmental protection, and economic growth in the agriculture sector.
Increased Productivity: IoT-driven precision agriculture leverages advanced sensors, data analytics, and automation to optimize farming practices tailored to specific field conditions. By precisely monitoring soil health, moisture levels, weather patterns, and crop growth, farmers can apply water, fertilizers, and pesticides more accurately, reducing waste and improving crop health.
The targeted interventions can increase crop yields by approximately 20-25%, making agriculture more productive, sustainable, and capable of meeting the growing global food demand efficiently (See McKinsey, 2016 for details).
Resource Efficiency: IoT helps optimize water, fertilizer, and pesticide use by providing real-time data on soil moisture, nutrient levels, and pest presence. For example, soil moisture sensors can trigger irrigation systems only when needed, preventing overwatering and conserving water.
Fertilizer applications can be adjusted based on nutrient sensors, ensuring plants receive precise amounts and reducing runoff and pollution. Pest detection sensors can identify infestations early, allowing targeted pesticide use only where necessary. These practices minimize environmental impact while enhancing crop health and productivity.
Risk Management: IoT enhances early detection of pests, diseases, and weather threats by utilizing sensors and data analytics to monitor crop conditions continuously. For example, a study by IBM and the University of Illinois demonstrated that IoT-enabled sensors could detect early signs of pest infestations and plant diseases, allowing farmers to take targeted action before widespread damage occurs.
Similarly, weather sensors can provide real-time forecasts of extreme weather events, such as frosts or storms, enabling farmers to implement protective measures. According to a report by MarketsandMarkets (2020), early detection and intervention through IoT can reduce crop losses by up to 30%, significantly improving yield stability and farm profitability (MarketsandMarkets, 2020).
Cost Reduction: Automation and precise resource application, as highlighted by the (See FAO, 2018 for details), enable farmers to perform tasks such as watering, fertilizing, and pest control more efficiently. By using IoT devices and automated systems, inputs are applied only where and when needed, reducing waste and labor costs.
This targeted approach minimizes resource consumption, lowers energy and input expenses, and streamlines farm operations, ultimately decreasing overall operational costs and increasing profitability while promoting sustainable farming practices.
Fields of Application of IoT in Agriculture
IoT in agriculture spans various fields, including precision farming, irrigation management, soil monitoring, crop health assessment, livestock tracking, and weather forecasting. It enables real-time data collection and analysis, improving resource efficiency, crop yields, and sustainability.
Precision Farming
Precision farming is an advanced agricultural approach that uses GPS, IoT sensors, and data analytics to optimize crop production. It enables farmers to monitor soil health, moisture levels, and crop conditions in real time, allowing for targeted application of water, fertilizers, and pesticides.
Soil monitoring: Sensors measure moisture, pH, and nutrient levels to determine optimal planting and fertilization schedules. Studies indicate that smart irrigation can reduce agricultural water consumption by 30-50% compared to conventional practices (See article by Mallareddy et al., 2023).
Variable Rate Technology (VRT): Adjust seed, fertilizer, or pesticide application rates based on real-time data, maximizing efficiency. IoT optimizes VRT by collecting real-time data through sensors and connected devices embedded in fields, machinery, and equipment.
There are different types of sensors- sensors for soil moisture, pH, temperature, nutrients, electrical conductivity, soil pollutants, insect/pest, plant stress, and positional and motion (See article by Monsoor et al. 2025 for details).
Crop Monitoring and Management
Crop monitoring and management using IoT involves deploying sensors to track soil moisture, temperature, and crop health in real time. This data helps farmers detect issues early, optimize irrigation, fertilization, and pest control, and improve yields. IoT enhances decision-making, reduces resource waste, and promotes sustainable practices in crop production
Remote Sensing and Drones: Equipped with multispectral cameras, drones play a crucial role in monitoring crop health by capturing images across various spectral bands beyond visible light. These images help detect early signs of stress, such as nutrient deficiencies, disease outbreaks, or water shortages that may not be visible to the naked eye.
For example, multispectral drone imaging was used in vineyards to identify vine stress early, allowing targeted interventions that improved yield and quality (See article by Miller et al., 2020 for details). By providing high-resolution, real-time data, drones enable precise decision-making, reduce the need for extensive ground surveys, and optimize resource application. This technology enhances sustainable farming practices and increases efficiency in large-scale agricultural operations (For more on drones, read the article by Guebsi et al. 2024; https://doi.org/10.3390/drones8110686).
Disease and Pest Detection: IoT-enabled devices analyze images and environmental data to predict outbreaks. Drone-based IoT systems were effective for controlling rice pests in India and China (See review article by Subramanian et al. 2021 for details).
Livestock Management
IoT enhances livestock management by using sensors to monitor animal health, activity, and environmental conditions in real time. Wearable devices track vital signs, detect illnesses early, and improve breeding decisions.
Environmental sensors optimize feed, water, and shelter conditions, reducing waste and enhancing productivity. Overall, IoT enables more efficient, healthier, and sustainable livestock farming through data-driven insights and proactive management.
Health Monitoring: The integration of sensors and devices used in precision livestock farming (PLF) with IoT technologies creates a network of connected objects that improve the management of individual animals through data-driven decision-making processes (See Tangorra et al. 2024 for details). Such technology is used in Australia and other countries.
Supply Chain Optimization
Food waste in the supply chain mainly occurs at the production source (11%), during processing and packaging (18%), in catering procurement management (12%), and at distribution and retail (5%). The 5% loss during distribution alone means that €7.15 million worth of food doesn’t reach consumers (See RIFCARD for details). IoT can optimize supply chains by providing real-time tracking of goods, inventory levels, and transportation conditions.
Traceability: Sensors play a crucial role in tracking product conditions from farm to table by continuously monitoring factors like temperature, humidity, and storage environment. For example, the radio frequency identification (RFID) tag can be attached to food packaging for contactless identification and tracking of products.
Predictive Maintenance: IoT devices continuously monitor machinery and equipment by collecting data on vibration, temperature, and performance metrics. This proactive approach detects potential faults early, enabling predictive maintenance.
Preventing unexpected breakdowns reduces downtime, increases operational efficiency, and lowers repair costs, ensuring smooth and reliable production processes. For example, Food companies like Walmart use IoT to trace produce, reducing waste and recall times (Walmart Sustainability Report, 2019).
Future Outlook and Challenges
The future of IoT technology promises increased connectivity, smarter automation, and enhanced data-driven decision-making across industries. While IoT’s potential in agriculture is vast, challenges remain:
Connectivity issues in remote rural areas
Connectivity issues in remote rural areas remain a significant challenge globally, impacting access to digital services, education, healthcare, and economic opportunities. These regions often lack infrastructure such as fiber optic cables, cellular towers, and reliable internet providers, resulting in limited or no connectivity.
India: Despite rapid growth in urban internet access, rural India still faces significant connectivity gaps. Only about 50% of rural households have internet access compared to over 80% in urban areas (TRAI, 2022). The lack of broadband infrastructure hampers digital inclusion efforts.
Sub-Saharan Africa: Many rural communities rely on unreliable mobile networks or satellite internet, which can be expensive and have high latency. For example, in Kenya, rural areas often depend on 2G networks, limiting access to modern internet services (World Bank, 2020, for details).
United States: Rural broadband deployment faces challenges due to high infrastructure costs and low population density. The Federal Communications Commission (FCC) reports that approximately 23% of rural Americans lack access to fixed broadband service, compared to 1.5% in urban areas (See FCC, 2021 for details).
High upfront costs for sensors and infrastructure
High upfront costs for sensors and infrastructure pose significant barriers to adopting IoT solutions across industries. These costs include purchasing sensors, setting up network infrastructure, and integrating systems, which can be substantial, especially for small and medium-sized enterprises. For example-
Manufacturing Sector: Implementing IoT sensors in manufacturing plants requires significant investment in industrial sensors, data analytics platforms, and network infrastructure. According to McKinsey (2021), deploying IoT in manufacturing can cost between $50,000 and $250,000 per factory, depending on scale and complexity.
Agriculture: Precision agriculture for smallholder farmers is progressing rapidly, yet costly for many farmers. A complete drone solution (including the analytics software, training modules, and charging equipment) could amount to $5,000, which is unaffordable for most farmers in low- and lower-middle-income countries (See UNDP, 2021 for details).
Smart Cities: Infrastructure projects like smart lighting or traffic management systems require extensive investment in sensors, cameras, and communication networks. For example, deploying smart street lighting in Los Angeles cost approximately $4 million initially (City of Los Angeles, 2019).
Data security and privacy concerns
Data security and privacy concerns are among the most critical challenges associated with the adoption of digital technologies, especially in IoT, cloud computing, and big data environments. As organizations and individuals increasingly rely on interconnected systems, the risk of data breaches, unauthorized access, and misuse of sensitive information escalates. Examples are:
IoT Devices in Healthcare: Connected medical devices collect sensitive patient data. In 2017, a cyberattack on the UK’s National Health Service (NHS) involved ransomware that compromised patient records and hospital operations (NHS Digital, 2017). Such breaches highlight vulnerabilities in securing health data.
Smart Home Devices: Consumer IoT devices like smart thermostats and security cameras often have inadequate security measures. In 2016, the Mirai botnet exploited poorly secured IoT devices to launch massive DDoS attacks, affecting major internet services (KrebsOnSecurity, 2016).
Data Privacy Regulations: The European Union’s General Data Protection Regulation (GDPR), implemented in 2018, emphasizes data privacy rights. Companies failing to comply face hefty fines, illustrating the importance of secure data handling (European Commission, 2018).
Need for farmer education and training
The need for farmer education and training is essential to enhance agricultural productivity, promote sustainable practices, and enable farmers to effectively utilize modern technologies such as precision agriculture, IoT, and data analytics. Education empowers farmers with knowledge about best practices, resource management, and new innovations, ultimately leading to increased yields and improved livelihoods. Examples are:
Digital Agriculture Training in India: The Indian government has launched initiatives like the Digital India program, which includes training farmers on using smartphones and apps for weather updates, market prices, and crop management (See book by Chadda et al. 2024).
Farmer Field Schools in Africa: The FAO’s Farmer Field School (FFS) approach has successfully trained farmers on integrated pest management and sustainable farming techniques. In Kenya, FFS led to a 25% increase in maize yields and better pest control (FAO, 2019).
Precision Agriculture Workshops in the US: Extension services in the United States conduct workshops on using GPS-guided equipment and soil sensors. These trainings help farmers optimize input use and reduce costs (USDA, 2018).
Prospects and Obstacles of IoT-Based Agriculture in Bangladesh
IoT-based agriculture holds significant potential for improving productivity, sustainability, and market access in Bangladesh. However, infrastructural, financial, and knowledge barriers need to be addressed to realize its full benefits.
Nonetheless, the Bangladesh Agricultural Research Council (BARC) has initiated IoT pilot projects to monitor paddy fields, but widespread adoption remains limited due to the above challenges (BARC, 2021).
Prospects
The prospects of IoT in Bangladesh agriculture include enhanced crop yields, efficient resource management, real-time monitoring, and sustainable farming practices, which can boost farmers’ productivity and income while promoting environmental conservation.
Enhanced Productivity and Efficiency: IoT devices such as soil sensors, weather stations, and automated irrigation systems can optimize resource use for higher yields. However, adoption of IoT in agriculture is not yet widely popular in Bangladesh, where most of the farmers still depend on traditional crop production (See article Ifti et al. 2023 for details).
Real-Time Data for Decision-Making: IoT provides farmers with timely information on soil moisture, weather forecasts, and pest outbreaks, enabling proactive actions. This can reduce crop losses and improve income stability.
Sustainable Farming: IoT facilitates precision agriculture, minimizing the overuse of water, fertilizers, and pesticides, thus promoting environmentally sustainable practices (See Hossain 2022 for works on nutrient management).
Market Access and Traceability: IoT can improve supply chain transparency, helping farmers access better markets and fair prices.
Obstacles
Obstacles in adopting IoT in Bangladesh agriculture include limited internet connectivity, high technology costs, lack of technical skills, and data security concerns. These challenges hinder the widespread implementation and effective utilization of IoT solutions among farmers.
Limited Infrastructure and Connectivity: Bangladesh faces challenges with internet penetration, especially in rural areas. According to the Bangladesh Telecommunication Regulatory Commission (BTRC, 2022), rural internet coverage remains inadequate, hindering the deployment of IoT.
High Costs and Affordability: IoT devices and maintenance costs can be prohibitive for smallholder farmers, who constitute the majority in Bangladesh.
Lack of Technical Knowledge: Farmers and local technicians often lack the awareness and skills to operate IoT systems effectively.
Data Security and Privacy Concerns: As IoT relies on data collection, concerns over data privacy and security may impede adoption.
FAQs
What is IoT in agriculture?
IoT in agriculture refers to the use of internet-connected sensors, devices, and machines to collect real-time data on farm conditions, enabling smarter decision-making and automation.
How does IoT improve crop monitoring?
IoT sensors monitor soil moisture, temperature, humidity, and light levels, allowing farmers to track crop health and growth, detect stress early, and optimize inputs like water and fertilizer.
What are smart irrigation systems?
Smart irrigation systems use IoT sensors and weather data to deliver water only when and where it's needed, reducing water waste and increasing efficiency.
Can IoT help in pest control?
Yes. IoT devices can detect pest presence or favorable conditions for pests, allowing farmers to take targeted and timely action, minimizing pesticide use.
What role does IoT play in livestock management?
IoT wearables monitor livestock health, location, activity, and feeding patterns, improving animal welfare, early disease detection, and farm productivity.
What are the economic benefits of IoT in agriculture?
IoT reduces input costs, minimizes waste, increases yields, and improves supply chain efficiency, leading to higher profits for farmers.
How does IoT help in climate-smart agriculture?
IoT tools provide climate data and early warnings, support adaptive strategies, and enhance resource use efficiency, helping farmers cope with changing weather patterns.
What are some real-world examples of IoT in agriculture?
Examples include John Deere’s smart tractors, India’s Nano Ganesh irrigation controllers, and IBM’s Watson Decision Platform for crop insights.
Conclusions
The high upfront costs for sensors and infrastructure hinder the widespread adoption of IoT. Overcoming this challenge requires cost-effective sensor technologies, government incentives, and scalable deployment strategies to make IoT solutions accessible for various sectors.
Farmer education and training are crucial for adopting modern agricultural practices, increasing productivity, and ensuring sustainability. Continuous education programs, tailored to local contexts, are vital for empowering farmers to meet the challenges of contemporary agriculture.
Despite the above-stated hurdles, ongoing innovations and decreasing costs are making IoT increasingly accessible, promising a smarter, more sustainable future for agriculture and global food security.