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Smart sensor and monitoring technology aims to sustainably increasing agricultural productivity and incomes

Nowadays, agricultural industry was forced to face several problems, such as lack of manpower, insufficient manual recording accuracy, difficulty in monitoring crop physiological mechanisms. To solving those technical problems, we propose this project developing biological monitoring technology and service systems of production and marketing for agriculture. Each development was based on Taiwanese agricultural and digital technology, such as Internet of Things, intelligent equipment, big data analysis and intelligent sensing system, to stabilize production quality and enhance the brand value of Taiwan's agricultural products.

In this project, the technical development is divided into four major areas, including agricultural UAV application system, big data analysis, expert system, and non-destructive detection technology. In the field of UAV application, drones were developing for crop monitoring and agricultural spraying, which are applied to crops such as rice, pineapple, head lettuce and broccoli. To stabilize the quality of agricultural products, the team introduce non-destructive detection technology. For instance, hyperspectral imaging techniques were helping to early detecting Fusarium wilt on Phalaenopsis and providing quality inspection for king oyster mushroom manufacturers before shipment. Two expert systems, “The expert system for pests and diseases management on agricultural” and “Field disease early warning microclimate composite module”, can simplify the operation process and time of field disease detection to achieve early diagnosis of diseases in the agricultural industry. The Intelligent image monitoring system is currently used to automatic identified pests in the greenhouse and monitor broiler house for flat feeding in order to reduce the burden on staff and provide managers with warning functions. In addition, the artificial intelligence computing capabilities work with the Internet of Things to improve the accuracy and immediacy of agricultural information broadcast services.

Smart farming is a management concept focused on providing the agricultural industry with the infrastructure to leverage advanced technology – including big data, the cloud and the internet of things (IoT) – for tracking, monitoring, automating and analyzing operations. This project promotes the prediction rate of disease diagnosis up to 60%, also increase crop productivity and reduce production costs by 20%.



Eustoma, Indian jujube and custard apple plant switching spectral light source module

Long-day crops use night lighting in fall and winter to adjust the growth rate and promote (or delay) flowering and fruiting rates in order to obtain higher yields. Conventional light sources (such as high-pressure sodium lamps, spiral light bulbs, etc.) are mostly used to fill light for plant at night. However ,The spectrum of conventionall light sources are mostly fixed wavelengths, which are mainly used for living lighting. Therefore, the lower light source utilization ratio leads to increase in electricity bills. This technology can adjust the spectrum of light at crop various growth stages (such as seedling stage, growth stage or flowering stage).

The Warning System of Sunburned Citrus

The warning system of sunburned citrus uses the micro-meteorological information to predict the fruit surface temperature of citrus. It can provide the sunburn degree through the FST threshold of sunburned citrus, and the real-time enviromental information in the citrus field. And then send alerts to remind citrus farmers to dispatch workers and chemical control by line app.

Expert System For Plant Diseases And Insect Pests Management

Through Expert System For Plant Diseases And Insect Pests Management, farmers can judge pests and diseases independently and control in crop cultivation. On the other hand, using the system background, experts can easily integrate their own research. Through background editing system, it can become exquisite web information, inherit the research crystallization and effectively teach the farmers to apply the research and development directly, which is helpful for the implementation of agricultural safety production. Reduce the use of pesticides, reduce food safety and other issues. In addition, the Line pest consulting helper and the pest information collection APP have been developed.

Unmanned plant protection machine intelligent path spraying system

After the lotus rose out of the water, the height of lotus was taller than the human, making it very difficult to apply pesticides manually. Working in an unventilated paddy field, the temperature is high, the mud is not easy to walk, and the physical loss is increased, and the inhaled pesticides have also increased relatively, resulting in a decrease in farmers’ willingness to spray pesticides, and the control efficacy of the chilli thrips has become worst. herefore, if spraying can be carried out through UAV, it will increase farmers' willingness to prevent and control. Use drones to collect lotus field images and establish variable spraying grids to accurately determine the application mode of each small field area, and finally directly integrates them into the drone's control system for real-time adjustments to achieve the purpose of accuracy and agriculture and pesticide reduction.

The Diseases Early Warning System with Field Microenvironment Sensing Mechanism-Example of Onion Field

The occurrence of crop diseases often directly affects the economic income of farmers. If we can predict the probability of crop disease by means of changes in the microenvironment of crops in the field, and prevent and control them in advance, it will reduce farmers' drug expenditures and disease losses. By collecting a large number of parameters such as field environmental factors during the growth of onion crops, and through the theoretical basis of crop disease, this system provides systematic intelligent learning and prediction of crop disease probability, reminding farmers of disease control and application, reducing agricultural losses and increasing yields.

Intelligent Pest Monitoring System and Its Digital Services

The Intelligent Pest Monitoring System was developed by integrating the advanced technologies including AI image recognition, embedded systems with high-speed computation capability and communication functions, cloud and mobile computing, and machine learning. The system can identify various types of insect pests and the counts on the sticky paper trap mounted on the intelligent sensing module. This allows long term monitoring of the status of insect pests as well as the environmental conditions automatically. The collected data thus can be used to build insect behavior models and therefore an early warning system can be implemented which will facilitate the greenhouse or field crop management. We anticipate this new approach and digital service will have multiple benefits in integrated pest and disease management and will thus reduce pesticide use, environmental impacts, crop loss, and labor in crop management and production.

Aquaculture environmetal detection with artifical intelligence manufaturing decision system

1.The environmental monitoring and risk forewarning platform:The results of environmental test will automatically upload to save manual efforts.
2.The intelligent production decision platform: Quickly get solutions for your problem from experts to achieve successful aquaculture.
3.Risk decision-making cases will be characterized into storage and tracking for future similar experiences, which improve the risk management and efficiency of experience inheritance.