Carbon emissions present a pressing challenge to the traditional construction industry, urging a fundamental shift towards more sustainable practices and materials. Recent advances in sensors, data fusion techniques, and artificial intelligence have enabled integrated digital technologies (e.g., digital twins) as a promising trend to achieve emission reduction and net-zero. While digital twins in the construction sector have shown rapid growth in recent years, most applications focus on the improvement of productivity, safety and management. There is a lack of critical review and discussion of state-of-the-art digital twins to improve sustainability in this sector, particularly in reducing carbon emissions. This paper reviews the existing research where digital twins have been directly used to enhance sustainability throughout the entire life cycle of a building (including design, construction, operation and maintenance, renovation, and demolition). Additionally, we introduce a conceptual framework for this industry, which involves the elements of the entire digital twin implementation process, and discuss the challenges faced during deployment, along with potential research opportunities. A proof-of-concept example is also presented to demonstrate the validity of the proposed conceptual framework and potential of digital twins for enhanced sustainability. This study aims to inspire more forward-thinking research and innovation to fully exploit digital twin technologies and transform the traditional construction industry into a more sustainable sector.

Molecular Communication (MC) is a promising micro-scale technology that enables wireless connectivity in electromagnetically challenged conditions. The signal processing approaches in MC are different from conventional wireless communications as molecular signals suffer from severe inter-symbol interference (ISI) and signal-dependent counting noise due to the stochastic diffusion process of the information molecules. One of the main challenges in MC is the high computational complexity of the existing time-domain ISI mitigation schemes that display a third-order polynomial or even exponential growth with the ISI length, which is further exasperated under the high symbol rate case. For the first time, we develop a frequency-domain equalization (FDE) with lower complexity, capable of achieving independence from the ISI effects. This innovation is grounded in our characterization of the channel frequency response of diffusion signals, facilitating the design of receiver sampling strategies. However, the perfect counting noise power is unavailable in the optimal minimum mean square error (MMSE) equalizer. We address this issue by exploiting the statistical information of the transmit signal and decision feedback for noise power estimation, designing novel MMSE equalizers with low complexity. The FDE for MC is successfully developed with its immunity to ISI effects, and its signal processing cost has only a logarithmic growth with symbol length in each block.

Water distribution networks are critical infrastructures under threat from the accidental or intentional release of contaminants. Data collection sensors remains challenging in underground spaces and large networks. In order to quantify the threat of contamination to end users, inferring contaminant spread with minimal sensor data is critical. Existing sensor deployment optimisation approaches use numerical optimisation, but suffer from scalability issues and lack performance guarantees. Analytical graph theoretic approaches link complex network topology (e.g. Laplacian spectra) to optimal sensing locations, but neglects the complex fluid dynamics. Alternative data-driven approaches such as compressed sensing offer limited sample node reduction. In this work, we introduce a novel data-driven Graph Fourier Transform that exploits the low-rank property to optimally sample WDNs. The proposed GFT allows us to recover the full dynamics of network contamination using only data sampled at a subset of nodes. It offers attractive improvements over existing numerical, compressed sensing, and graph theoretic approaches. Our case study results show that, on average, with nearly 30% of the junctions monitored, we are able to fully recover the networked dynamics. The framework is useful beyond the application of WDNs and can be applied to a variety of infrastructure sensing for digital twin modeling.

The development of reconfigurable intelligent surfaces (RIS) has recently advanced the research of physical layer security (PLS). Beneficial impacts of RIS include but are not limited to offering a new degree-of-freedom (DoF) for key-less PLS optimization, and increasing channel randomness for physical layer secret key generation (PL-SKG). However, there is a lack of research studying how adversarial RIS can be used to attack and obtain legitimate secret keys generated by PL-SKG. In this work, we show an Eve-controlled adversarial RIS (Eve-RIS), by inserting into the legitimate channel a random and reciprocal channel, can partially reconstruct the secret keys from the legitimate PL-SKG process. To operationalize this concept, we design Eve-RIS schemes against two PL-SKG techniques used: (i) the CSI-based PL-SKG, and (ii) the two-way cross multiplication based PL-SKG. The channel probing at Eve-RIS is realized by compressed sensing designs with a small number of radio-frequency (RF) chains. Then, the optimal RIS phase is obtained by maximizing the Eve-RIS inserted deceiving channel. Our analysis and results show that even with a passive RIS, our proposed Eve-RIS can achieve a high key match rate with legitimate users, and is resistant to most of the current defensive approaches. This means the novel Eve-RIS provides a new eavesdropping threat on PL-SKG, which can spur new research areas to counter adversarial RIS attacks.

Molecular networking has been identified as a key enabling technology for Internet-of-Nano-Things (IoNT): microscopic devices that can monitor, process information, and take action in a wide range of medical applications. As the research matures into prototypes, the cybersecurity challenges of molecular networking are now being researched on at both the cryptographic and physical layer level. Due to the limited computation capabilities of IoNT devices, physical layer security (PLS) is of particular interest. As PLS leverages on channel physics and physical signal attributes, the fact that molecular signals differ significantly from radio frequency signals and propagation means new signal processing methods and hardware is needed. Here, we review new vectors of attack and new methods of PLS, focusing on 3 areas: (1) information theoretical secrecy bounds for molecular communications, (2) key-less steering and decentralized key-based PLS methods, and (3) new methods of achieving encoding and encryption through bio-molecular compounds. The review will also include prototype demonstrations from our own lab that will inform future research and related standardization efforts.

Precise timing over timestamped packet exchange communication is an enabling technology in the mission-critical industrial Internet of Things, particularly when satellite-based timing is unavailable. The main challenge is to ensure timing accuracy when the clock synchronisation system is subject to disturbances caused by the drifting frequency, time-varying delay, jitter, and timestamping uncertainty. In this work, a Robust Packet-Coupled Oscillators (R-PkCOs) protocol is proposed to reduce the effects of perturbations manifested in the drifting clock, timestamping uncertainty and delays. First, in the spanning tree clock topology, time synchronisation between an arbitrary pair of clocks is modelled as a state-space model, where clock states are coupled with each other by one-way timestamped packet exchange (referred to as packet coupling), and the impacts of both drifting frequency and delays are modelled as disturbances. A static output controller is adopted to adjust the drifting clock. The H∞ robust control design solution is proposed to guarantee that the ratio between the modulus of synchronisation precision and the magnitude of the disturbances is always less than a given value. Therefore, the proposed time synchronisation protocol is robust against the disturbances, which means that the impacts of drifting frequency and delays on the synchronisation accuracy are limited. The one-hour experimental results demonstrate that the proposed R-PkCOs protocol can realise time synchronisation with the precision of six microseconds in a 21-node IEEE 802.15.4 network. This work has widespread impacts in the process automation of automotive, mining, oil and gas industries.