Physical-layer security (PLS) schemes use the randomness of the channel parameters, namely, channel state information (CSI) and received signal strength indicator (RSSI) to generate the secret keys. There has been limited work in PLS schemes in long-range (LoRa) wide-area networks (LoRaWANs) which hinder their widespread application. Limitations observed in existing studies include the requirement of high correlation between channel parameter measurements for secret key generation in the proposed schemes and the evaluation of the schemes has only been done in either fully indoor or outdoor environments. The real-world wireless sensor networks (WSNs) and LoRa use cases might not meet both requirements thus making the current PLS schemes inappropriate for these systems. By considering the limitations found in existing PLS schemes, this article proposes LoRA-LiSK, a practical and efficient shared secret key generation scheme for LoRa networks. Our proposed LoRa-LiSK scheme consists of several preprocessing techniques (timestamp matching, two sample Kolmogorov–Smirnov tests, and a Savitzky–Golay filter), multilevel quantization, information reconciliation using Bose–Chaudhuri–Hocquenghem (BCH) codes, and finally, privacy amplification using secure hash algorithm SHA-2. The LoRa-LiSK scheme is extensively evaluated on real WSN/IoT devices in practical application scenarios: 1) indoor to outdoor and 2) LoRa static and mobile outdoor links. It outperforms existing schemes by generating keys with channel parameter measurements of low correlation values (0.2–0.6), while still essentially achieving high key generation rates, and low key disagreement rates (10%–20%). The scheme updates a key in approximately 1 h using an application profile with high transmission rate compared to 3 h reported by existing works while still respecting the duty cycle regulation. It also incurs less communication overhead compared to the existing works.

Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.