On 8 May at 10:15, Farooq Ayoub Dar will defend his doctoral thesis „Autonomous Pervasive Sensing for Proactive Environmental Sustainability“ to obtain the degree of Doctor of Philosophy (in Computer Science).
Supervisor
Associate Prof. Huber Raul Flores Macario, University of Tartu
Opponents
Prof. PhD Mario Di Francesco, Aalto University (Finland)
Prof. PhD. Claudio Bettini, University of Milan (Italy)
Summary
Advancements in pervasive sensing and autonomous systems are revolutionizing environmental monitoring by enabling real-time, scalable, and high-resolution data collection. However, challenges remain in integrating diverse sensing modalities, processing voluminous data efficiently near the source, and deploying cost-effective autonomous platforms suitable for complex terrestrial and underwater environments. This thesis addresses these challenges by proposing innovative solutions that blend sensing, fog computing, and autonomous systems to enhance environmental sustainability efforts.
Three core contributions are presented. First, MIDAS, a novel thermal dissipation–based sensing modality, which enables accurate, contactless material characterization of everyday objects and waste, improving recycling and resource management practices. Second, LIZARD, an autonomous plastic litter monitoring pipeline combining thermal and optical sensing, capable of detecting macro-, meso-, and micro-plastics with energy-efficient machine learning integrated on ground drones for scalable pollution mapping. Third, a micro-cloud fog computing framework built from cost-effective commercial-off-the-shelf devices, providing decentralized underwater data processing capabilities that overcome communication and infrastructure limitations in remote aquatic environments.
Through extensive experimental validation and real-world deployments, these contributions demonstrate significant improvements in monitoring accuracy, energy efficiency, and system scalability. Together, they establish a comprehensive ecosystem of sensing and computing technologies that empower faster, data-driven decisions for environmental management. This work paves the way for proactive stewardship of ecosystems, addressing pollution challenges, and supporting global sustainability goals through innovative technological integration.
