This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by-step guide to developing a unique EEW network architecture driven by a Software-Defined Wide Area Network (SD-WAN)-based hole-punching technology consisting of MEMS-based, low-cost accelerometers hosted by the general public. In contrast with most centralised cloud-based approaches, a node-level decentralised data-processing is used to generate warnings with the support of a modified Propagation of Local Undamped Motion (PLUM)-based EEW algorithm. With several hypothetical earthquake scenarios, experiments were conducted to evaluate the system latencies of the proposed decentralised EEW architecture and its performance was compared with traditional centralised EEW architecture. The results from sixty simulations show that the SD-WAN-based hole-punching architecture supported by the Transmission Control Protocol (TCP) creates the optimum alerting conditions. Furthermore, the results provide clear evidence to show that the decentralised EEW system architecture can outperform the centralised EEW architecture and can save valuable seconds when generating EEW, leading to a longer warning time for the end-user. This paper contributes to the EEW literature by proposing a novel EEW network architecture.

Purpose: The purpose of this paper is to introduce an integrated laboratory experiment setup (ILES) to overcome problems encountered in open distance learning (ODL) especially when offering engineering degree programmes. Design/methodology/approach: Engineering laboratory experiments can be classified as experiments which are performed with the intention to inculcate theory, and second, to provide hands-on experience. The ILES integrates both types of experiments with face-to-face laboratory (FFL), online remote laboratory (ORL), and multimedia demonstrations, and it helps to reduce traditional FFL duration by 50 per cent. The first phase of the ILES provides an opportunity to refer multimedia demonstrations of the experiments. Thereafter, students attend the first FFL session, which covers about 25 per cent of the experiments. In the next step, 50 per cent of the experiments are offered using the ORL, via the internet while interacting with real equipment and making actual observations. The final step is used to accomplish the rest of the experiments (25 per cent) in FFL which facilitates the clarification of any problem that may occur in the ORL. Findings: This blended laboratory system will help to achieve ODL objectives while utilising resources productively and cost effectively. Having implemented the idea and based on the information received from the stakeholders, this has proved to be a workable solution to one of the difficulties faced by ODL students. Research limitations/implications: The level of outcome of the students has to be observed and analysed in comparison with the traditional laboratory setup. Practical implications: Some experiments (e.g. thermodynamics) which need more safety precautions are difficult to offer via ORL. Originality/value: The ILES is a blended setup including FFL, ORL and multimedia demonstrations and it is a novel concept which is most applicable to engineering/science programmes offered in ODL mode.

At present, people have a tendency to carry out higher education in a distance mode due to their busy lifestyles. However, open and distance learning (ODL) educational organizations encounter difficulties when delivering laboratory experiments. This paper presents the development of an online laboratory platform as a solution. It can be used to deliver laboratory experiments, using electronic components and instruments such as a signal generator and oscilloscope. Students are able to perform experimental tasks remotely utilizing real equipment and components. The system users can view laboratory environments via a camera which provides a sense of reality.The platform provides facilities to customize and rebuild the laboratory experiments according to the requirements of the organization. It can also be utilized as a useful educational tool to acquire pre-experience before entering the real laboratory. Thestatistical analysis shows no significant difference between the face-to-face laboratory (FFL) and online remote laboratory (ORL) experimental results within a 95% confidence level.The system can enhance the existing open and distance learning system by sharing the resources in a flexible manner.This system reduces the difficulties that distance learning students encounter when participating in FFL sessions. It also reduces the number of FFL sessions and is helpful to working students. One of the main objectives of ODL is to provide a learning environment for those who missed the opportunity for higher education for a variety of reasons. This system will help to achieve this objective.

The emergence of Industry 4.0 has resulted in a rapid increase in the demand for bandwidth due to the proliferation of the industrial Internet of Things (IIoT). Increased utilization of the network also gives rise to undesirable consequences such as high latency and increased likelihood of data loss through packet drops. Encoding inputs using event-based sampling is a potential solution for decreasing network traffic generated when continuous input variables are sampled. The problem addressed by this article is the fact that currently there is no effective method for comparing different encoders. The resulting contribution is the use of mutual information to compare the input and encoded output in terms of accuracy for the currently most efficient encoders that use either memory based event triggering (MBET) or deadband error modulation (DEM). This allows a practitioner to select a suitable encoder for a given input specification.

Earthquake early warning (EEW) can reduce injuries and damage by issuing alerts before incoming shaking. We evaluate the Propagation of Local Undamped Motion (PLUM) algorithm as a candidate for a national EEW system for Aotearoa New Zealand (NZ). We develop and demonstrate a novel methodology for evaluating EEW performance under a wide range of future earthquake scenarios using a synthetic earthquake catalogue. We used a 220,000‐year‐long physics‐based synthetic earthquake catalogue of NZ and generated synthetic seismograms using deterministic ground‐motion simulations. The algorithm was tested in the Canterbury and Wellington regions for alert correctness and timeliness, the effects of different warning radii and robustness to sensor/telemetry failures. The PLUM algorithm works well in highly populated areas of Canterbury, but not as effectively in some southern parts of Wellington City, due to the lack of stations in Cook Strait to provide warnings for earthquakes centred south of Wellington. Performance is also weaker in rural areas of both regions because the station density is too low. In Canterbury, PLUM provided correct timely alerts (warning time > 0 s) for more than 70% of moderate shaking events (probability of correct timely alert; PrCTA ≥ 70%) over 100‐year intervals in 88% of the high‐population areas. All grid cells with PrCTA < 50% were in low‐population areas. In Wellington, 89% of grid cells with PrCTA < 50% were in low‐population areas, and two‐thirds of high‐population grid cells achieved PrCTA ≥ 70%. Results suggest an appropriate choice of PLUM warning radius for the current NZ network would be 40–60 km, wider than the original 30 km radius designed for Japan. The algorithm performs well in Canterbury, but Wellington may require further enhancement to the sensor network. The study also demonstrates the robustness of the algorithm under simulated sensor or communication breakdowns, particularly in regions with high seismic instrument density.