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This technology is based on the automated production of green lacewings. By integrating this automated system with an intelligent production scheduling system, we have developed a precise predictive model for identifying spatiotemporal hotspots of farmer demands for natural enemies. This approach ensures that green lacewing egg products are stably produced reasonable priced, and environmental friendly, thereby incentivizing farmers to adopt these natural enemy products. Consequently, this stimulates the biological control industry, creates an economically viable supply chain for pesticide alternatives, and aligns with the policy trend of pesticide reduction.
Sustainability | AgricultureThe coffee bean sorting tray developed by this technology enables the automatic selection and synchronous sorting of green coffee beans into multiple tracks, thereby improving bean sorting efficiency. The tray's unique design features buffer columns that prevent coffee beans from clumping together as they enter the multiple tracks. Additionally, dust-fall holes allow dust on the beans to fall through during the sorting process, reducing dust contamination on the beans entering the sorting machine.
Sustainability | AgricultureAn automatic portable detection system for pathogenic bacteria includes a water inlet and outlet device, a miniature mixing device, and a detection chip. Through a micro-pump, sample water and multiple reagents are sequentially injected into the microchip for mixing, generating an analyte solution and initiating a color reaction. The detection chip is responsible for detecting the color depth of the analyte solution, converting it into a corresponding voltage value, and generating a test result upon completion of the color reaction.
Sustainability | Agriculture1.It can instantly identify various types of materials on the conveyor, and can subdivide materials such as paper, plastics, metal cans, etc., and can identify colors, uses and specific brands. 2.An industrial six-axis robotic arm uses a vacuum method to suck objects and spray them to a designated location. It has a small space to use and is quick to set up. It can quickly replace a person's standing position. 3.After AI identification, the types and quantities of various resource recycling materials are presented digitally; displays on various operating platforms (computers, mobile phones, tablets) are provided to understand the latest production line material status regardless of time and region.
Sustainability | Green Energy ＆ EnvironmentThe brown planthopper, a major pest affecting rice crops in Taiwan, particularly during the second cropping season, can cause hopper burn, leading to significant yield losses. This technology aims to address this issue by providing farmers with a timesaving, experience-independent tool for early BPH detection and control. It leverages smartphone cameras to capture rice plant images, which are then analyzed using AI deep learning algorithms to identify BPH characteristics. The technology generates actionable recommendations for effective pest control strategies based on these analyses, forming the foundation of a BPH early warning system.
Sustainability | AgricultureThe cloud-based automated interpretation system with algorithmic assistance for chemicals residue detection, developed by the Agricultural Chemicals Research Institute, Ministry of Agriculture(ACRI), streamlines the analysis of mass spectrometry data. This significantly reduces analysis time. For instance, the "Method of Test for Pesticide Residues in Foods-Multiresidue Analysis (5)", which typically requires 5-10 hours for manual analysis of 20 samples, can now be completed within 10 minutes using this system. The technology also provides an information platform to aid in result interpretation and has the potential for future applications in detecting veterinary chemicals, pharmaceuticals, food additives, heavy metals, and other contaminants, thus greatly enhancing inspection efficiency.
Sustainability | AgricultureThe " Dairy cow health management decision analysis system" is a comprehensive platform integrating thermal imaging for disease detection, key health and performance indicators, and automated environmental monitoring. It provides data analysis for milk yield, quality, reproduction, and disease, with features including: 1. Intelligent mobile management. 2. Early identification and warning of mastitis and fever. 3. Automated heat stress-based cooling system activation.
Sustainability | AgricultureScales and insect eggs lodged in the crevices of fruits pose a significant challenge to fruit export quarantine procedures in our country. Traditional removal methods, such as fumigation, detergents, and alcohol washing, disrupt the waxy layer of scales but can negatively impact fruit quality and flavor. High-pressure water washing, while effective, can cause physical damage, reducing the fruit's commercial value. This technology presents a solution by integrating image data analysis with an automated micro-carbonated pulse cleaning system for fruits and vegetables. This approach effectively removes up to 100% of scales without causing any damage to the fruit's texture.
Sustainability | AgricultureThe system utilizes air-blower as the power source for the feeding machine, paired with a movable feeding turret to accurately deliver feed to designated points. By incorporating laser and weight sensors, it can measure both the amount of feed dispensed and the remaining quantity. Equipped with AI-based splash recognition technology and 5G network connectivity, the feeding machine enables intelligent decision-making, cloud data uploading, and remote control capabilities.
Sustainability | AgricultureThis technology aims to mitigate challenges within the broccoli industry, such as concentrated harvest seasons, high susceptibility to environmental fluctuations, and elevated mechanized production costs. By integrating crop physiology data, environmental parameters, and product specification management, coupled with AIoT and UAV-based spectral vegetation index analysis, an intelligent broccoli cultivation management module has been developed. Preliminary results indicate that this module achieves a prediction accuracy for broccoli flowering and harvesting periods within ±4 days, respectively. Moreover, yield prediction accuracy reaches an impressive 94%.
Sustainability | AgricultureThis research builds a smart workplace monitoring module by integrating image recognition technology, environmental sensors, etc. to prevent risky behaviors such as dangerous driving behaviors, high temperatures, or drinking alcoholic refreshing drinks. This research technology includes: A: Intelligent image recognition B: Environmental sensing: temperature and alcohol C: Management and warning platform It can be used in mechanical equipment such as tower cranes, excavators, cranes and driving vehicles in the construction industry to provide effective management solutions for occupational safety and health in the construction industry and reduce the risk of occupational disasters.
Sustainability | Machinery ＆ SystemRice leaf blast, a significant threat to rice yields during Taiwan's first cropping season, can be devastating. This technology employs unmanned aerial vehicles (UAVs) equipped with multispectral cameras to capture field imagery and analyze spectral data, enabling early detection of the disease. By identifying plants at risk and visualizing affected areas, it empowers farmers to make informed decisions regarding pesticide application, optimizing its use and minimizing environmental impact.
Sustainability | AgricultureProvides basic education courses on labeling and hazard communication of hazardous chemicals, practical courses on the regulations for labeling and hazard communication of hazardous chemicals, wastewater tank bottom sludge removal operations, sewer sludge removal operations, chemical facilities pipeline maintenance operations, and chemical storage tank maintenance. The platform includes six units of multi-language (Vietnamese, Indian, English) virtual space somatosensory education and training materials (with 13 units available in Chinese). The total operation time is approximately 120 minutes.
Sustainability | Life ApplicationIn order to solve the problem of thermal hazards caused by high temperatures in summer, the Labor Safety Research Institute of the Ministry of Labor (and the research team Daren University of Science and Technology) developed the "Multifunctional Ice Cooling Vest" specifically for outdoor heat dissipation protective gear, which can greatly reduce the physiological workload caused by thermal hazards. The technical (product) features of the "Multifunctional Ice Cooling Vest" include:. A "Thermoelectric cooling chip" and "turbo fan" form an ice-sensing refrigeration mechanism group. B. "Fan jacket" and "Cooling jacket" are multifunctional and innovatively designed vest sets. Use the ice cooling mechanism set to be installed in the innovatively designed multi-functional vest of "Fan jacket" and "Cooling jacket". By wearing the vest, you can feel the ice cooling airflow and blow it to the human body to create a cooling effect, providing outdoor workers with a cooling effect. Heat dissipation and cooling protection equipment.
Sustainability | AgricultureThis technology addresses the issues commonly encountered in the traditional transportation of natural enemies, such as damage and breakage due to compression. It also mitigates the challenges faced prior to release, where unhatched eggs are susceptible to climate fluctuations or predation. The material utilized in this technology is bagasse, and the application method has been enhanced from manual lid opening to heat sealing, significantly improving packaging efficiency and user-friendliness.
Sustainability | AgricultureThe system automatically collects chicken vocalizations within the poultry house using integrated microphones and embedded systems. These recordings undergo audio processing and machine learning analysis to differentiate normal chicken sounds from abnormal ones, such as those indicative of disease. This provides poultry farmers with early warnings of potential infectious disease outbreaks.
Sustainability | AgricultureIn order to prevent accidents during the hoisting operation of cranes, a safety control monitoring system has been developed. The system uses an intelligent image recognition technology to monitor dangerous areas during operation, which includes range setting, monitoring objects (events) within the range, and subsequent triggering of message pushes, alarms, system alerts, and so forth. The technology is expected to be further promoted and applied to the monitoring of various dangerous areas on construction sites, such as windows, elevator openings, shafts, stairwells, etc., as well as areas where the risk of falling may occur during labor operations.
Sustainability | Information ＆ CommunicationsTo address the significant damage caused by beet armyworm <Spodoptera exigua> infestations in scallion crops during hot, dry summers, a predictive model has been developed based on meteorological factors. This model enables forecasting of pest outbreaks up to 10 days in advance, with a threshold prediction accuracy exceeding 80%. By integrating these forecasts with comprehensive beet armyworm management strategies, growers can proactively implement targeted control measures, thereby mitigating potential crop losses.
Sustainability | AgricultureComing soon!
