Feb 06, 2026

UMC’s 10th Eco Echo Award Recognizes Projects from Smart Pest Control to Low-Carbon Water Treatment

UMC held the 10th edition of the Eco Echo Award in November, which was open for the first time to graduate students and academic research groups. The longstanding award aims to encourage environmental solutions with future potential and long-term impact, focusing on climate adaptation, ecological conservation, and resource recycling. This year's winners have leveraged their expertise and research to provide actionable solutions for local environmental issues, especially in sustainable agriculture and water resource management.

 

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Beehive Data Technology:Controlling noctuid moth pests through smart data

Beehive Data Technology introduced a pest control system to repel moth pests. Using Sanxing in Yilan County , they noted a 40% drop in scallion yields due to beet armyworms, causing an estimated NT$300 million loss. The "Noctuid Warning and Smart Counterattack System” they developed  includes pest warnings, a smart nighttime watering system, and a weather-monitoring control platform. This system helps farmers anticipate pest outbreaks, precisely control watering and spraying, and is estimated to improve pest control efficiency by 10% while reducing pesticide use by 10%.

 

MR Agroecology Ltd.:Co-existing with apple snails to protect biodiversity

Ecologists Lin Fang-Yi and Chen Yi-Han initiated the "Co-farming with Apple Snails" project in Yilan to protect paddy field biodiversity. In 2021, they launched the "Large Rice Seedling Transplantation Service," covering 40 hectares. Transplanting rice seedlings at the 4-5 leaf stage reduces crop damage by apple snails by 45% due to the coarse fiber of the large seedlings. Additionally, with proper field management, apple snails can help control weeds, significantly reducing weeding labor.

 

Center for Space and Remote Sensing Research, National Central University:Creating a smart and sustainable digital twin water treatment solution

The team launched the "Low-Carbon Precision Dosing Digital Twin" project, using machine learning to create a coagulation reaction model. By testing various operational combinations, the project aims to find the lowest cost and carbon emission methods that meet water quality standards. Field tests show it can save over 30% on chemical costs, reduce electricity costs by 80%, and cut carbon emissions by 20%. Integrating digital twin technology, the project provides real-time water quality predictions and operational recommendations.

 

Working together to protect Taiwan's environment

Driven by environmental concerns, these three winning teams have applied their ideas in real-world settings, using scientific data and technological innovation. They have provided innovative solutions and valuable research for agricultural sustainability and wastewater treatment, showing that co-existing with the environment is essential to protect our home.

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