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Decentralised protocol-independent automation in smart buildings


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Abstract

Providing automation and reacting in time are primary functions of a modern smart building. That is done thanks to sensors and actuators distributed across the architecture. Smart building devices employ a diverse set of communication protocols, and the number of such devices grows every year. A typical modern Building Automation System (BAS) is not prepared to effectively handle that growing amount of heterogeneous data and represents a single point of failure as well as a potential source of congestion and unacceptable delays. Most BAS platforms run automation workflows over IP-based networks, making non-IP protocols, such as Low-Power Wide Area Networks (LPWAN), incompatible with building automation services. Existing solutions for integrating non-IP wireless protocols into smart building automation are ineffective as reduce application performance, increase latency and drain sensor battery life. A centralised approach also assumes aggregation of sensor data from the entire building at a single point, potentially infringing occupants privacy.

This dissertation proposes a decentralised, IP-agnostic approach for improving efficiency and robustness of smart building automation. By offloading BAS functions to a hierarchy of smart gateways (SGWs), the system manages device interoperation and provides seamless building automation in a decentralised manner, irrespective of the underlying communication protocols. This can be achieved as traditional gateways are underutilised and can provide automation and interoperation logic on top of their basic functions. The decentralised architecture, by its nature, also has a potential for improving occupant privacy and security through edge protection. The dissertation demonstrates the feasibility, efficiency, and robustness of the decentralised automation compared to the classic centralised BAS approach, by evaluating its prototype within realistic MQTT automation scenarios involving 300 LoRaWAN and Wi-Fi sensors and actuators. The dissertation also introduces tools and techniques for large-scale evaluation and presents a concrete example of SGW privacy-preserving threat protection, aimed at enhancing building occupants' security and privacy.

Description

Date

2023-09-29

Advisors

Mortier, Richard

Qualification

Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge

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Except where otherwised noted, this item's license is described as All Rights Reserved