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Here’s the second blog in our two-part series on the electrification of agriculture. In this instalment, we take a closer look at the technologies powering this transformation and discuss how Bulgin is contributing with its heavy-duty connectors. If you missed the first part, be sure to check it out for an introduction to the topic and the challenges involved.

Electrification of agriculture part 2: An intelligent approach to agriculture

What happens if you combine artificial intelligence (AI) and the internet of things (IoT) with sensors, robotics and drones in agriculture? The answer is very efficient farming that makes the most of resources while maximising the output. This blog will focus on the technologies involved in modern agriculture and discuss concepts such as precision agriculture and predictive analytics.

AI and data analytics

AI plays a key role in modern farming by processing large volumes of site-specific data – collected by sensors, drones and satellites – as well as market trends, weather conditions and historical yield records to uncover patterns and correlations that would have otherwise been missed. This helps farmers monitor weather, soil and crop conditions in real time, and even make informed decisions on which crops to cultivate and when to sow them.1,2 Combining AI with machine learning (ML) gives rise to predictive analytics, which can forecast pest infestations and disease outbreaks, as well as provide guidance on optimal planting and harvesting times. These insights allow farmers to make data-driven decisions, improving irrigation, fertilisation and pest control.

AI not only benefits farming practices but also streamlines the agricultural supply chain; AI-driven systems optimise route planning, inventory management and distribution, ensuring that fresh produce reaches the shelves quickly and efficiently.1

Sensors

Gathering the necessary data for AI and ML processing would not be possible without reliable sensors. There are many different types of sensors that can be used in agriculture,1 including

  • acoustic sensors that monitor pests and water levels by detecting sound and vibrations;
  • electromagnetic sensors that measure soil properties such as moisture and organic matter;
  • electrochemical sensors to track plant growth and environmental pollutants;
  • optical sensors that monitor crop health and nutrient levels;
  • and ultrasonic sensors that measure water levels and monitor underwater growth of aquatic plants for harvest timing.

Drones and robotics

Drones equipped with AI and precision sensors are also important tools for gathering data, providing aerial views of agricultural fields, and helping farmers to monitor crop health, soil moisture and pest activity. Drones fitted with hyperspectral, thermal or multispectral imaging can pinpoint crop stress, sickness and arid regions needing attention, so that farmers can tailor irrigation, fertilisation and pest control efforts more efficiently. Similarly, they can help with vegetation index calculations and monitoring of irrigation, giving farmers a better understanding of crop health and energy emissions, and helping them to make the most of their resources.

Autonomous robots, such as tractors and harvesters, are becoming far more common too, automating tasks like planting, weeding and harvesting. AI-powered vision systems, robotic arms and computer vision algorithms allow these machines to identify ripe crops, assess their freshness, size and quality, and harvest them with precision, reducing waste and damage.3

Connecting everything

What all these technologies have in common is that they rely on electronic components – such as heavy-duty connectors, switches and indicators – for energy supply and data management. Our robust, sealed connectors provide reliable protection against the harshest of external elements like water, dust, chemicals and extreme temperatures, and we also manufacture switches and indicators designed for heavy-duty farming vehicles and equipment. Our products help drive efficiency, productivity and sustainability in agriculture, letting farmers make smarter decisions, and get more out of their resources while keeping pace with the growing global demand for food.

References

1)RajakA. GangulyS. Adhikary and S. Bhattacharya. Internet of Things and smart sensors in agriculture: Scopes and challenges. Journal of Agriculture and Food Research. 2023 (24). doi:10.1016/j.jafr.2023.100776

2)SN Kothuri, et al. Precision Agriculture Advisor. Research Square Preprint. doi.org/10.21203/rs.3.rs-4677379/v1

3)Mishra, J. Das and R. Awtar. An Emerging Era Of Research In Agriculture Using AI. Journal of scientific research and technology. 2024 (2). doi:10.61808/jsrt93

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