Smart Agriculture Technologies and Application Case Studies

HSI,YU-CHIEN（China Productivity Center Agricultural Innovation Department I）

1. Introduction

Given the continued growth of the global population, rapid technological advancement, and the intensifying impacts of climate change, traditional agriculture is facing numerous challenges, such as the reduction of arable land, demographic shifts in rural areas, deterioration of labor shortages, and the frequent occurrence of extreme weather events. These factors have led to rising risks in agricultural production, posing a significant threat to global food security.

In addition, as awareness of the impacts of climate change, resource scarcity, and biodiversity loss continues to increase, issues such as sustainable development and net-zero carbon emissions have gradually become key global concerns.

To respond to these changes in the industrial environment and to enhance the competitiveness of the agricultural sector in Taiwan, the Ministry of Agriculture has aligned with national policy to implement “New Agriculture” initiative under the “Five Plus Two Industry Innovation Plan”. The Smart Agriculture Program commenced in 2017 and have achieved many substantial technological R&D results. Through the Smart Agriculture Achievement Diffusion Project, subsidies have been provided to support industrial upgrading and assist businesses in adopting relevant technological breakthroughs, thereby facilitating the practical application of innovative technologies within the industry. These efforts have helped farmers improve production efficiency, reduce production risks and costs, enhance agricultural management models, and increase overall industry value.

Smart agriculture is an innovative farming model that integrates cross-disciplinary advanced technologies, including information and communication technology (ICT), Internet of Things (IoTs), big data analytics, and blockchain. It aims to enhance agricultural productivity and reduce resource waste through real-time monitoring of crop conditions and precise management of farmland environments. The following section presents three real-world case studies to demonstrate the diverse applications of smart agricultural technologies in Tiawan and the tangible benefits they bring.

2. Case Studies of Smart Agriculture Achievement Diffusion
1. Zhan Shian Agricultural Biotechnology Co., Ltd.

Zhan Shian Agricultural Biotechnology Co., Ltd. (hereinafter referred to as “Zhan Shian”), established in 2016, has over 15 years of management experience. It is the largest supplier of beef tomatoes in Taiwan, with a total area of contracted cultivation area exceeding 60 hectares and an annual production of more than 8,000 metric tons. Zhan Shian supplies tomatoes to domestic and international well-known brands and major retail chains, such as McDonald’s, Subway, and Costco. To ensure every tomato meets market standards, Zhan Shian has been proactive in the introduction of smart technologies into its cultivation management to increase the proportion and volume of tomatoes meeting specifications requirements.

Tomatoes are a seasonal crop, primarily grown on the plains of Taiwan. Due to high market demand and concentration of harvest periods, there are significant fluctuations between peak and off-peak seasons. During off-seasons, production must be supplemented by mountainous regions. However, variations in environmental factors such as temperature, humidity, and sunlight across different farmland areas lead to unstable yields of market-grade produce, thereby affecting overall production value of tomatoes and income of farmers.

Furthermore, traditional cultivation practices rely heavily on accumulated experience or paper-based records, making it difficult to preserve and pass on valuable expertise. Coupled with the impacts of climate change, these factors pose significant challenges to maintaining consistent product quality and stable returns in the tomato industry.

Supported by the resources under the Smart Agriculture Achievement Diffusion Project in 2023, Zhan Shian Agricultural Biotechnology collaborated with Ling Cheng Technology Co., Ltd. to deploy the JoinFarm – Smart Agriculture Production Management System. The development of the functions such as tomato production capacity analysis and forecasting, production timetables, weather alert mechanisms, light quantum measurement, Growing Degree Days (GDD) production models, and dashboards for analyzing flowering schedules, fruit sets, and market-grade ratios has been completed. Rolled out to 15 implementation sites, this system balances seasonal production fluctuations, stabilizes tomato prices and yields, connects to production and sales traceability systems, and improves production and management efficiency.

Meanwhile, field monitoring equipment has been installed at three flatland sites to capture the changes of real-time environmental data in order to mitigate agricultural losses caused by extreme weather. During the project implementation period, this initiative successfully increased tomato production value by NT$15.5 million, saved 675 labor hours, and reduced labor costs by NT$190,800.

2. Weatherangel Decision Information Co., Ltd.

Weatherangel Decision Information Co., Ltd. (hereinafter referred to as Weatherangel Decision Information), established in 2014, specializes in provision of meteorological services. By integrating data and delivering precise forecasts, the company helps industries across Taiwan reduce losses and increase efficiency. Since 2019, Weatherangel Decision Information has been focusing on the development of smart agriculture, launching the “SkyEye Farm Station,” which integrates field monitoring systems, weather forecasting, and decision-support tools. Together with its “Weather Detective” service, the company provides farmers with real-time environment monitoring, warnings for imminent rainfalls & disasters, and hourly weather forecasts for up to 16 days.

There are approximately 24 major types of economic fruit crops in Taiwan, with citrus accounting for the largest harvest area (13.8%). However, adverse climate conditions such as continuous rainfall, typhoon seasons, and intermittent extreme sunlight and heat can easily cause fruit damage. If farmers rely solely on conventional wisdom and experience to determine the timing of pesticide application, preventive efficacy will be limited. In combination with insufficient flexibility of labor availability, these challenges increase the difficulty of agricultural production.

Supported by the resources under the Smart Agriculture Achievement Diffusion Project in 2023, Weatherangel Decision Information has developed “Microclimate Joint Observation System.” Connected with the Sunburn Forecasting and Warning System operated by Taiwan Agriculture Research Institute, the “Weather Detective” Microclimate Joint Observation System has established the Sunburn Prevention Guideline and the User Manual for the Sunburn Prediction and Reporting System to help farmers understand what causes fruit sunburn, how to prevent it, and how to operate the Sunburn Prediction and Reporting System interface.

In addition, the Joint Observation Network Command Dashboard Center has been put in place to assist managers in the organization and integration of images and growth data from multiple farmland sites. During the project period, 30 microclimate stations were deployed and installed across major citrus-producing regions in northern, central, and southern Taiwan. This helped to save up to 18,000 labor hours, cut down labor costs by NT$3.6 million, and reduce the cost associated with decision-making errors related to agricultural inputs by NT$3.628 million.

3. Fu-Chen Auto Technology Corporation

Fu-Chen Auto Technology Corporation (hereinafter referred to as “Fu-Chen Co.”), established in 2008, specializes in system integration and the development of automated production equipment, and is committed to providing innovative solutions for smart agriculture, fishery, and livestock farming. Fu-Chen Co. has more than eight years of extensive experience in the R&D and manufacturing of intelligent equipment. Its main products include water quality monitoring devices, smart environmental control systems, microclimate monitoring stations, early warning systems, and remote app-based monitoring solutions. In recent years, the company has further developed intelligent recognition and feeding systems and smart feed dispensers. These products and solutions have been widely adopted by smart agriculture sites in Taiwan, and the results have been remarkable.

Factors such as the aging workforce, the declining birth rates and the soaring feed costs have contributed to the impending gap in the passing on of aquaculture knowledge and experience and continued to squeeze the profitability of the aquaculture industry. Traditional automatic feeders typically operate on fixed schedules according to farmers’ experience, and require constant manual patrol inspection to prevent overfeeding and the resulting deterioration of water quality and increased production risks. In addition, production and sales traceability records are mostly based on approximate feeding volumes, and there is a lack of digitalized management data. This coupled with the limited number of domestic manufacturers supplying labor-saving aquaculture machinery makes it difficult to deploy smart solutions at scale.

Supported by the resources under the Smart Agriculture Achievement Diffusion Project in 2024, Fu-Chen Co. acquired the “Underwater Fish Activity Imaging and Sensing Analysis System” through a technology transfer from the Fisheries Research Institute under the Ministry of Agriculture. Building on this, the company established an edge AI computing system, integrated and upgraded its existing smart feed dispensers, and successfully developed an “Edge AI Feed Dispensing Machine.” This system combines remote monitoring with edge AI computing to automatically and precisely control feed weights and upload data to a cloud database. Its app-based remote configuration supported by camera monitoring sends out alerts for insufficient feed and abnormal conditions.

During the project implementation period, seven mass-produced Edge AI Feed Dispensers were installed at field sites for validation. Over a three-month validation period, the system helped save 86 labor hours, reduce feed costs by NT$28,251, and increase company revenue by NT$2.45 million.

3. Practical Challenges and Reflections on Adoption of Smart Agriculture

The Smart Agriculture Program has now entered its eighth year, covering a wide range of industry sectors and placing strong emphasis on the development of innovative technologies. Although the R&D phase involved demonstration sites to ensure optimization of system design and operational processes through discussions and field testing, many technological achievements have yet to be effectively disseminated. The scope of applications remains largely confined to isolated sites. Validation by more sites and accumulation of practical experience are required to establish mature business models.

In addition, the adoption of smart agriculture technologies is often accompanied by challenges such as difficulty of equipment maintenance, non-intuitive user interfaces, and high initial investment costs. Sometimes extensive training is required to operate the systems effectively. These factors contribute to a conservative attitude among farmers in general toward smart agriculture. The general belief that existing practices are still sufficient to meet production has impeded the motivation to introduce new technologies.

Therefore, future initiatives should consider how to continue the alignment between scientific innovation and industry needs, strengthen collaboration among industry, academia, and research institutions, and establish a robust mechanism for diffusion of achievements. This will deepen the industry’s sustainable operation and practical application after the deployment of smart agriculture technologies.

To enhance the dissemination of agricultural machinery-related achievements, it is advised to encourage industry players to test and assess the performance of such agricultural machinery and include these machinery tools in subsidy programs administered by the Agriculture and Food Agency. For IoT-based environmental control equipment and systems, it is necessary to involve relevant units of the Ministry of Agriculture and local governments for discussions and joint planning, so as to integrate available subsidy resources to promote adoption. Furthermore, technology service providers are recommended to develop implementation solutions consisting of small modules so that farmers may deploy technologies in phases as needed. This will lower initial investment costs and increase willingness to adopt smart equipment.

4. Conclusion

The promotion of smart agriculture not only showcases Taiwan’s capabilities in R&D and innovation of agricultural technology, but also represents a key solution to global challenges related to food security and sustainable development. From Zhan Shian’s tomato production management, Weatherangel’s weather forecasts and citrus sunburn warning systems, to Fu-Chen Co.’s smart aquaculture solutions, each case study demonstrates how technology can revitalize traditional agriculture. Smart technologies improve agricultural productivity effectively, stabilizes farmers’ income and lays an important foundation for sustainable development of agriculture.