Ramin Soleymani-Fard

ORCID: 0000-0001-8510-5845
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About
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Research Areas
  • Climate change impacts on agriculture
  • Climate Change, Adaptation, Migration
  • Species Distribution and Climate Change
  • Indigenous Studies and Ecology
  • Video Surveillance and Tracking Methods
  • Energy Efficient Wireless Sensor Networks
  • Environmental law and policy
  • Cryospheric studies and observations
  • Climate Change Communication and Perception
  • Climate variability and models
  • Modular Robots and Swarm Intelligence
  • Risk Perception and Management
  • Environmental Justice and Health Disparities
  • Environmental and Cultural Studies in Latin America and Beyond
  • Robotic Path Planning Algorithms
  • UAV Applications and Optimization
  • Environmental Education and Sustainability
  • Distributed Control Multi-Agent Systems

Universitat Autònoma de Barcelona
2019-2024

University of Duisburg-Essen
2012

Leibniz University Hannover
2008

In the quest to improve understanding of climate change impacts on elements atmospheric, physical, and life systems, scientists are challenged by scarcity uneven distribution grounded data. Through their long history interaction with environment, Indigenous Peoples local communities have developed complex knowledge systems that allow them detect in environment. The study protocol presented here is designed 1) inventory based 2) test hypotheses global spatial, socioeconomic, demographic...

10.1371/journal.pone.0279847 article EN cc-by PLoS ONE 2023-01-05

Abstract The effects of climate change depend on specific local circumstances, posing a challenge for worldwide research to comprehensively encompass the diverse impacts various social-ecological systems. Here we use place-specific but cross-culturally comparable protocol document indicators and as locally experienced analyze their distribution. We collected first-hand data in 48 sites inhabited by Indigenous Peoples communities covering all zones nature-dependent livelihoods. documented...

10.1038/s43247-023-01164-y article EN cc-by Communications Earth & Environment 2024-01-09

Advances in the field of computer vision enable smart cameras to cooperatively analyse scenes without human intervention. Large networks autonomous, self-organising PTZ (pan, tilt, zoom) require algorithms and protocols that make way for cooperation between multiple (SCs). This paper introduces a distributed algorithm object tracking with SCs (DMCtrac). The focus lies on management issues arising large SC systems rather than algorithms. DMCtrac enables observe objects throughout an area...

10.1109/icdsc.2008.4635684 article EN 2008-09-01
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