6 papers
Beyond Peak TOPS/W: A System-Level Perspective on Hybrid Digital, Analogue and Neuromorphic Computing
Eiman Kanjo, Varuna De Silva
The digital revolution, which progressively replaced analogue methods with digital circuits, has entered a new phase as AI expands across cloud infrastructure, mobile networks, wea…
Node Learning: A Framework for Adaptive, Decentralised and Collaborative Network Edge AI
Eiman Kanjo, Mustafa Aslanov
The expansion of AI toward the edge increasingly exposes the cost and fragility of cen- tralised intelligence. Data transmission, latency, energy consumption, and dependence on lar…
A Multicore and Edge TPU-Accelerated Multimodal TinyML System for Livestock Behavior Recognition
Qianxue Zhang, Eiman Kanjo
The advancement of technology has revolutionized the agricultural industry, transitioning it from labor-intensive farming practices to automated, AI-powered management systems. In…
TrajAware: Graph Cross-Attention and Trajectory-Aware for Generalisable VANETs under Partial Observations
Xiaolu Fu, Ziyuan Bao, Eiman Kanjo
Vehicular ad hoc networks (VANETs) are a crucial component of intelligent transportation systems; however, routing remains challenging due to dynamic topologies, incomplete observa…
A Hybrid Edge Classifier: Combining TinyML-Optimised CNN with RRAM-CMOS ACAM for Energy-Efficient Inference
Kieran Woodward, Eiman Kanjo, Georgios Papandroulidakis +2
In recent years, the development of smart edge computing systems to process information locally is on the rise. Many near-sensor machine learning (ML) approaches have been implemen…
Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learning
Ziyuan Bao, Eiman Kanjo, Soumya Banerjee +2
With the growing computational capabilities of microcontroller units (MCUs), edge devices can now support machine learning models. However, deploying decentralised federated learni…