Special Sessions

The future of agriculture depends on the integration of advanced Industrial Internet of Things (IIoT) networks that enable real-time data acquisition, intelligent analytics, and adaptive decision-making. This talk will explore emerging IIoT architectures for sustainable agriculture, with a focus on high-speed, low-power sensor networks and resilient communication systems. It will highlight opportunities for scalable deployment, emphasising interoperable platforms that empower farmers, industrial processors and policymakers to optimise resource use, enhance productivity, and accelerate agritech innovation.

This talk will introduce the IoTBench a comprehensive benchmark framework designed to evaluate and compare the performance of low-power wireless IoT devices technologies, aiming to standardise performance metrics and guide future developments in IoT ecosystems.
 

Collection and analysis of data from deployed networks is essential for understanding communication networks. Collected traffic traces are used to classify network anomalies such as Internet worms, viruses, power outages, ransomware events, and infrastructure failures in times of conflict. Various anomaly and intrusion detection approaches based on machine learning have been employed to develop models based on collected datasets. The reported results indicate that while performance of machine learning models greatly depends on the used datasets, they are viable tools for detecting the Internet anomalies.

Artificial Intelligence (AI) is poised to revolutionize society, yet its escalating energy demands pose a formidable challenge to its long-term sustainability. The staggering gap in energy consumption between biological (Human Brain @20watts) and artificial intelligence (ChatGPT @100KWatts) is striking. My research aims to bridge this gap with a bio-inspired, integrative approach, where algorithm-hardware co-design and neuromorphic computing converge to create intelligent, energy-efficient systems. In this talk, I will talk about my group’s recent efforts towards enabling and democratizing spike-based machine intelligence design, simulation, and evaluation across different applications.