Mini Workshop, 10 July 2026

Time: 2pm – 4pm Friday July 10th
Location: MCS 2068

Talk 1: Swarm Navigation and Sensing – from Classroom to Real-World Missions

Abstract: Robotic swarms are transforming how we explore and monitor challenging environments, from volcanic terrains and deep sea on Earth to lava tubes beneath the lunar surface. By combining decentralized wireless networking, precise localization, and environmental sensing, autonomous robots and sensors can collaboratively measure, estimate and adapt without relying on GPS, cellular networks or other external infrastructure.

This talk will introduce the fundamentals of robotic swarm localization and sensing, explains how compact swarm systems are built at the German Aerospace Center (DLR), and showcases their usage as a hands-on gateway to modern signal processing, sensor fusion, and cooperative robotics as well as their deployment in space-analogy missions.

Speaker: Dr. Siwei Zhang, Institute of Communications and Navigation, German Aerospace Center (DLR)

Talk 2: Building Intelligent Environmental Monitoring Systems for Extreme Environments

Abstract: Remote and extreme environments, such as forests, mountains, deserts, and disaster-prone regions, present unique challenges for environmental monitoring due to limited connectivity, scarce energy resources, and difficult operating conditions. Collecting reliable data in these settings requires a combination of sensing technologies, resilient communication systems, and intelligent data-processing capabilities that can operate with minimal infrastructure.

This talk explores how IoT technologies can be used to acquire, transmit, integrate, and analyze environmental data from heterogeneous sources. Particular attention is given to communication solutions for remote deployments, including Low-Power Wide-Area Networks (LPWANs) such as LoRaWAN, which enable long-range and energy-efficient data transmission where conventional network infrastructure is unavailable.

The presentation also discusses the integration of external data sources through REST APIs and MQTT-based systems, enabling the combination of local sensing data with weather, satellite, and other environmental information.

A key focus of the talk is the use of TinyML to bring intelligence directly to resource-constrained devices. By executing machine learning models at the edge, sensor nodes can perform local anomaly detection, event classification, and data filtering, reducing communication requirements, extending battery lifetime, and enabling faster responses to critical situations. Through examples in environmental monitoring and disaster mitigation, the presentation highlights how the combination of IoT, LoRaWAN, edge intelligence, and multi-source data integration can support more scalable, resilient, and autonomous monitoring systems.

Speaker Biograph:

Pietro Manzoni is a computer engineering professor at the "Universitat Politècnica de València," Spain. He received a master’s degree in computer science from the "Università degli Studi" of Milan, Italy, in 1989, and a Ph.D. in Computer Science from the "Politecnico di Milano,"

Italy, in 1995. From November 1992 to February 1993, he interned at Bellcore Labs, Red Bank, New Jersey, USA. From February 1994 to November 1994, he was a visiting researcher at the ICSI (International Computer Science Institute), Berkeley, California, USA, and from May 2021 to July 2021, he was a visiting professor at the University of Bologna, Italy.

His research focuses on the Internet of Things by designing intelligent sensing and data-driven systems that utilize TinyML-enabled sensors for local inference and autonomous decision-making. He focuses on how IoT devices collect, process, and distribute data efficiently across large-scale deployments, particularly for environmental intelligence. A key part of his work involves developing robust connectivity solutions using LPWAN technologies and Pub/Sub architectures to support reliable data dissemination in resource-constrained settings. He also investigates complementary communication models to create resilient, integrated connectivity across the edge–cloud continuum.

He is the coordinator of the Computer Networks Research Group (GRC), a senior member of the IEEE, a Technical Board member of the IEEE Technical Committee on Hyper-Intelligence, a Founding member of the IEEE SIG on Metaverse, and a member of the ACM SIGCAS - Computers and Society.