Abnormality Detection and Localization Schemes using Molecular Communication Systems: A Survey
Abnormality detection and localization (ADL) have been studied widely in wireless sensor networks (WSNs) literature, where the sensors use electromagnetic waves for communication. Molecular communication (MC) has been introduced as an alternative approach for ADL in particular areas such as healthca...
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Zusammenfassung: | Abnormality detection and localization (ADL) have been studied widely in
wireless sensor networks (WSNs) literature, where the sensors use
electromagnetic waves for communication. Molecular communication (MC) has been
introduced as an alternative approach for ADL in particular areas such as
healthcare, being able to tackle the shortcomings of conventional WSNs, such as
invasiveness, bio-incompatibility, and high energy consumption. In this paper,
we introduce a general framework for MC-based ADL, which consists of multiple
tiers for sensing the abnormality and communication between different agents,
including the sensors, the fusion center (FC), the gateway (GW), and the
external node (e.g., a local cloud), and describe each tier and the agents in
this framework. We classify and explain different abnormality recognition
methods, the functional units of the sensors, and different sensor features.
Further, we describe different types of interfaces required for converting the
internal and external signals at the FC and GW. Moreover, we present a unified
channel model for the sensing and communication links. We categorize the
MC-based abnormality detection schemes based on the sensor mobility,
cooperative detection, and cooperative sensing/activation. We also classify the
localization approaches based on the sensor mobility and propulsion mechanisms
and present a general framework for the externally-controllable localization
systems. Finally, we present some challenges and future research directions to
realize and develop MC-based systems for ADL. The important challenges in the
MC-based systems lie in four main directions as implementation, system design,
modeling, and methods, which need considerable attention from multidisciplinary
perspectives. |
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DOI: | 10.48550/arxiv.2207.06032 |