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Diego M. Jiménez Bravo
Spain
University of Salamanca
University
Artificial Intelligence, IoT, Edge Computing, FAIR Data, Smart Agriculture, Livestock Monitoring, Interoperability
Topic 1 - Data technologies and data management
We are looking to join a consortium as a technical partner (leading or participating in WPs related to Data Management, AI, or IoT). Our main focus is to apply our expertise in Edge Computing and Artificial Intelligence to build the data infrastructure for Topic 1.
We can contribute with:
1. Data Ingestion & Edge Processing: Designing IoT architectures that collect and pre-process data on-site (farms/machinery) to ensure quality and reduce latency before cloud integration.
2. Development of Robust AI Models: Creating and training Machine Learning/Deep Learning algorithms specifically designed for heterogeneous agricultural data (images, time-series, sensor logs).
3. FAIR Data Implementation: Ensuring that the data pipelines we build adhere to interoperability standards, facilitating data exchange between different platforms.
We bring the experience of 70+ industry projects, bridging the gap between academic research and real-world deployment.
We can contribute with:
1. Data Ingestion & Edge Processing: Designing IoT architectures that collect and pre-process data on-site (farms/machinery) to ensure quality and reduce latency before cloud integration.
2. Development of Robust AI Models: Creating and training Machine Learning/Deep Learning algorithms specifically designed for heterogeneous agricultural data (images, time-series, sensor logs).
3. FAIR Data Implementation: Ensuring that the data pipelines we build adhere to interoperability standards, facilitating data exchange between different platforms.
We bring the experience of 70+ industry projects, bridging the gap between academic research and real-world deployment.
Expert Systems and Applications Lab (ESALab) – University of Salamanca (Spain)
ESALab is a Recognized Research Group (GIR) at the University of Salamanca with a strong track record in applied Artificial Intelligence and Smart Systems. Our multidisciplinary team of 25+ researchers (Computer Science, Industrial, Electrical Engineers, and Statisticians) bridges the gap between raw sensor data and actionable insights.
Our Value Proposition for Topic 1: We offer expertise in the entire data lifecycle for agriculture and livestock, ensuring interoperability and robustness:
- Data Acquisition & IoT: Deployment of smart sensor networks in agricultural/livestock environments.
- Edge & Cloud Computing: Processing data at the edge (on-farm) to reduce latency and bandwidth, combined with Cloud scalability.
- Robust AI Models: Development of Machine Learning and Deep Learning algorithms tailored for noisy agricultural data.
- Data Management: Expertise in storage, integration, and processing of data, adhering to FAIR principles.
Previous Experience:
- Participation in over 70 industry-collaborative projects, ensuring technology transfer and real-world applicability.
- Experience in Precision Agriculture and Smart Livestock farming solutions.
- Development of commercializable products and internal tools for ag-tech companies.
Role in the Project: Technical Partner / Work Package Leader (AI Development, IoT Architecture, Data Processing).
ESALab is a Recognized Research Group (GIR) at the University of Salamanca with a strong track record in applied Artificial Intelligence and Smart Systems. Our multidisciplinary team of 25+ researchers (Computer Science, Industrial, Electrical Engineers, and Statisticians) bridges the gap between raw sensor data and actionable insights.
Our Value Proposition for Topic 1: We offer expertise in the entire data lifecycle for agriculture and livestock, ensuring interoperability and robustness:
- Data Acquisition & IoT: Deployment of smart sensor networks in agricultural/livestock environments.
- Edge & Cloud Computing: Processing data at the edge (on-farm) to reduce latency and bandwidth, combined with Cloud scalability.
- Robust AI Models: Development of Machine Learning and Deep Learning algorithms tailored for noisy agricultural data.
- Data Management: Expertise in storage, integration, and processing of data, adhering to FAIR principles.
Previous Experience:
- Participation in over 70 industry-collaborative projects, ensuring technology transfer and real-world applicability.
- Experience in Precision Agriculture and Smart Livestock farming solutions.
- Development of commercializable products and internal tools for ag-tech companies.
Role in the Project: Technical Partner / Work Package Leader (AI Development, IoT Architecture, Data Processing).