AioT Hub : Manchester

AIoTHub (formerly IoT North) Community meetup are pleased to present Suyash Joshi in "Physical AI at the Edge: Real Time Intelligence with Sensors and Data"

Abstract:
Physical AI brings intelligence into the real world through sensors and devices that observe, decide, and act in real time. Making this work requires processing data where it’s generated at the edge. In this talk, we’ll explore how Physical AI systems use real-time sensor data and edge computing to deliver low latency intelligence. The session includes a live edge AI Robotic demo, with open source code and hardware instructions on GitHub. You’ll leave with practical patterns for building realtime Physical AI systems at the edge.

Bio:
Suyash Joshi is a Senior Developer Advocate at InfluxData, focused on AI and data engineering. He brings 15 years of experience across Oracle, RingCentral and InfluxData. He regularly speaks at technical conferences on building practical, real-time systems that connect data to the physical world. In his free time, he leads the Magineer London meetup (3,400+ members) and serves as a UK STEM Ambassador.

AIoTHub (formerly IoT North) Community meetup are pleased to present Aditya Thakekar in "Federated Edge Intelligence for Decentralized Smart Grid Management"

Abstract:

​As cities transition toward renewable energy, the traditional centralized power grid is struggling to handle the volatility of solar and wind power, alongside the surging demand from Electric Vehicles (EVs). This topic explores the development of a Federated Edge Intelligence (FEI) system where IoT-enabled smart meters and EV charging stations act as "mini-brains" to manage local energy distribution without relying on a central cloud.

Bio:

Aditya thakekar, an Electronics engineer turned Embedded firmware consultant, currently a graduate student in London at New York University.

AIoTHub (formerly IoT North) Community meetup are pleased to present Professor Dhaval Thakker in "Responsible AI at the Edge: Challenges for Fairness, Explainability, and Assurance"

Abstract:
As AI systems move beyond centralised cloud infrastructures, Edge AI is becoming a critical part of real-time decision making in homes, hospitals, factories, and cities. This shift brings new opportunities for privacy, responsiveness, and local autonomy, but it also exposes unresolved challenges for Responsible AI. In this talk, Professor Thakker examines what happens when fairness, explainability, and assurance must be achieved in environments where data, models, and decisions are distributed across heterogeneous devices. Drawing on applied work, the talk sets out the emerging landscape of Responsible AI at the edge, highlighting practical lessons, open research questions, and a path towards systems that remain trustworthy even when intelligence is highly decentralised.

Bio:
Professor Dhaval Thakker is Professor of Artificial Intelligence and Internet of Things and Research Lead for the Department of Computer Science at the University of Hull, where he also leads the Centre for Responsible AI. His research bridges Responsible and Explainable AI, Edge Computing, and Human-Centred Systems, with applications spanning healthcare, social care, defense, circular economy, and critical infrastructure. He coordinates Hull’s engagement with the EPSRC-funded National Edge AI Hub, leading pilots on hybrid federated learning and dependable AI at the edge, and has extensive experience directing multi-partner innovation projects exceeding £15M, supported by funding bodies such as Innovate UK, EPSRC, the EU, and international collaborations across Asia, North America, Europe, and the Middle East.

AIoTHub (formerly IoT North) Community meetup are pleased to present TBA in "TBA"

Abstract:

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Bio:
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