Q: How is AIoT technology being applied in Precision Agriculture?
A: Experts predict that by 2050, the world’s population will grow to more than 9.5 billion, and the demand for food will increase by 70%. Coupled with the impacts from an aging population and climate change, food shortages could become a major issue. To counter these trends, smart agriculture needs to be pushed vigorously.
“Precision agriculture” was first developed in the 1990s. Based on VRT (Variable-rate technology) theory, using “agricultural map materials”, “GPS location on farming machines” and “the plant growth and harvest data” input, the VRT system performs planting, care, and harvesting. Just like the architecture of AI, it first collects data, then analyzes, then predicts, and finally executes, so it could be called the pioneer of smart agriculture.
Over the past few years, the technology has evolved, and many technologies have been applied in this industry. For example, AI robots can automatically identify crops and harvest them, or detect the proportion of pesticide residue in the soil, adjust the amount of pesticide use, and achieve sustainable use of agricultural land. Another example is a field soil sensors node that detects soil temperature, ph value and other parameters, allowing you to understand the current soil condition at the remote end to determine whether to re-water or fertilize. Smart monitoring & irrigation systems also make use of sensors and AI to control irrigation and avoid waste due to excessive water injection.
Q: How are drone technologies being used in smart farming?
A: The main labor force in traditional agriculture are the elderly and foreign workers because hard manual work scares young people away. Thus, local governments are trying to utilize new technology to help farmers increase efficiency in planting crops and feeding livestock. Agricultural drones are one such new technology that has become more and more common as the costs have dropped. Agricultural operators began by using drones to spread fertilizer and pesticide, reducing farmers’ contact with toxic materials and saving a lot of time. More recently, operators want to use drones to increase farming yield rates and crop quality, so technology companies are trying to add multiple high-resolution cameras on drones that will enable them to become like human eyes to inspect plant health in real-time, detect insects and weeds promptly (once they are equipped with machine vision and edge computing). These pictures will then be uploaded to the cloud for analysis, allowing farmers to not only optimize fertilizer and pesticide utility but increase yield rate and benefit environmental protection.
Q: How can AIoT be used to improve hydroponics?
A: Hydroponics is a new way of growing plants using nutrient solutions in water and without soil. It can save significant space to grow a vertical garden vs. traditional farming methods. In this way, we can also better protect plants and avoid many factors that could cause them damage. Both water and nutrients are fed directly to the root structure of the plants and recycled through the hydroponic system making it easy to block diseases and bugs from typical land and soil. The plants thrive on the nutrient solution alone – the medium merely acts as a support for the plants and their root systems. We can control and monitor the environment of hydroponic gardens through an IOT system that monitors the environment automatically. For example:
- Maintaining Proper Nutrient Solution Temperature: When temperatures get too high, dissolved oxygen levels go down and create an environment ripe for root rot. Temperatures that get too low will slow down plant growth. For small reservoirs, aquarium heaters are usually enough to warm up a nutrient solution that is too cold.
- Monitoring pH and EC in water: pH ranges should be kept in the 5.5-6.5 range and EC level between 1.2 to 2.0. Parameters should be adjusted for the variety of plant in your hydroponic garden.
- Adjusting light conditions: We can adjust suitable light wave length for particular plants and control shinning time.
- Air quality and temperature: Ventilation is necessary for good air quality. Smart control of fans can bring good air quality and keep the environment temperature in a suitable range.
Q: How are AI and machine learning transforming agriculture?
A: As the world population continues to grow, there’s an increase in the food demand worldwide. Although land and water resources are finite, we can still manage the production in a more sustainable and efficient way by using AI and machine learning in smart farming. For example, irrigation is a significant factor in determining the crop yield and has a direct impact on profits. A smart crop irrigation system is comprised of multiple sensors, central gateways and the sprinklers. The system uses machine learning to analyze soil moisture, measure the amount of water in leaves and predict the amount of rainfall in real time. AI-driven data analysis provides farmers with irrigation recommendations that take all the variables into account, including the geographical, climatic, and topological factors. In addition, image sensing technology can be applied to collect weather information for field control and pest defection. Using machine learning models and algorithms, images collected from the system enable farmers to adjust their crop strategies.
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