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bioRxiv · 10.64898/2026.03.17.712375

Semantic-Aware Energy-Efficient Operation inSmart Capsule Endoscopy

Zoofaghari, M.·Rahaimifard, A.·Chatterjee, S.·Balasingham, I.
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Abstract

Goal-oriented semantic communication has recently emerged in wireless sensor-actuator networks, emphasizing the meaning and relevance of information over raw data delivery, thereby enabling resource-efficient telecommunication. This paradigm offers significant benefits for intra-body or implantable sensor-actuator networks, including dramatic reductions in bandwidth requirements, latency, and power consumption. In this paper, we address a patch-based energy-efficient anomaly detection method for smart capsule endoscopy. We propose a deep learningbased algorithm that employs the similarity between features extracted from measured images and a reference (normal) image as the detection metric. The algorithm is evaluated using a clinical dataset of capsule-captured images, combined with a simulated intra-body channel model. The results demonstrate that even with only 60% of the transmission power (relative to a standard link design for QPSK modulation) and 65% of the light intensity, the probability of anomaly detection remains above 85%, and it gradually improves as power and illumination levels increase. This improvement translates into a potential battery life extension of over 43%. The findings highlight the potential of semanticaware, energy-efficient intra-body devices for more sustainable and effective medical interventions.

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Zoofaghari, M., Rahaimifard, A., Chatterjee, S., Balasingham, I.. 2026-03-19. Semantic-Aware Energy-Efficient Operation inSmart Capsule Endoscopy. https://doi.org/10.64898/2026.03.17.712375

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