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1. AI-Powered Solutions for Food Systems
식품 시스템에서의 AI 활용
1. AI-Powered Solutions for Food Systems
식품 시스템에서의 AI 활용
1.1. Deep learning-based rapid microbial detection
딥러닝 기반 미생물 조기 검출 모델 및 센서 개발
1.1. Deep learning-based rapid microbial detection
딥러닝 기반 미생물 조기 검출 모델 및 센서 개발
AI-based computer vision for microbial detection and classification
Development of real-time biosensors for microbial detection
1.2. Developing AI models specialized for food data
식품 데이터 특화 AI 모델 개발
1.2. Developing AI models specialized for food data
식품 데이터 특화 AI 모델 개발
Generative AI for food data enhancement
Optimizing AI model architectures for food-specific applications
AI-driven data augmentation for diverse food datasets
1.3. AI-based sensor for food quality prediction
AI 기반 식품 품질 센서 개발
1.3. AI-based sensor for food quality prediction
AI 기반 식품 품질 센서 개발
Developing a generalized AI-based sensor applicable to diverse food types and environmental conditions
Lightweight and robust algorithms for real-time on-site use
2. Process Simulation and Optimization
공정 시뮬레이션 및 최적화
2. Process Simulation and Optimization
공정 시뮬레이션 및 최적화
2.1. Computer simulation for process optimization
물리 기반 시뮬레이션을 통한 공정 설계 및 최적화
2.1. Computer simulation for process optimization
물리 기반 시뮬레이션을 통한 공정 설계 및 최적화
Physics-based computer simulation for food processing
Simulation-based decision-making for process improvements and designs
2.2. Digital twin using AI, simulations, and sensors
AI, 시뮬레이션, 센서를 활용한 디지털 트윈 구축
2.2. Digital twin using AI, simulations, and sensors
AI, 시뮬레이션, 센서를 활용한 디지털 트윈 구축
Real-time monitoring and adaptive process control
Virtual prototyping for system optimization
2.3. Food supply chain analysis & risk detection
식품 공급망 분석 및 위해 요소 탐지
2.3. Food supply chain analysis & risk detection
식품 공급망 분석 및 위해 요소 탐지
Scenario-based simulations for risk assessment and decision-making
Supply chain optimization to enhance efficiency, traceability, and sustainability
AI-driven food safety analysis for hazard identification and control
3. Smart Farm Systems
스마트팜 시스템 개발
3. Smart Farm Systems
스마트팜 시스템 개발
3.1. AI-based crop monitoring and disease detection
컴퓨터 비전 기반 작물 생육 모니터링 및 질병 감지
3.1. AI-based crop monitoring and disease detection
컴퓨터 비전 기반 작물 생육 모니터링 및 질병 감지
Real-time image analysis for plant growth and health assessment
Early detection of plant diseases using deep learning models
3.2. IoT-based environmental sensing and control systems
IoT기반 환경 센서 및 제어 시스템 개발
3.2. IoT-based environmental sensing and control systems
IoT기반 환경 센서 및 제어 시스템 개발
Integration of sensors for crop environment monitoring
Automated control of irrigation, lighting, and ventilation based on sensor feedback
Data-driven decision support for yield improvement and resource efficiency
4. Some projects are currently confidential
4. Some projects are currently confidential
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