Low Power Wide Area Network (LPWAN) has been one of the most widely applied wireless technologies supporting large-scale IoT applications in Industry 4.0 era. In which, 3 major LPWAN protocols play leading roles in actual deployments: Long Range (LoRa), NarrowBand-IoT (NB-IoT), and Sigfox. Currently, promoting interoperability among different LPWANs is regarded as an evolution for IoT constructions. Hitherto, there lacks of an industrial standard to produce multi-protocol LPWANs in systematical level, subsequently introduces challenges to interoperate LPWANs. To address this challenge, this article proposes an IEEE 2668 based LPWAN infrastructure to improve interoperability regarding the in-compliance issue raised by different LPWAN standards. Thus, an interoperable framework for LPWANs (IF-LPWANs) is presented to embrace and cooperate multiple LPWANs. The framework was tested to provide a 8.3% energy consumption reduction and a 13% PID transmission latency reduction. Such a development is the first of its kind in both industrial and research area.

Long Range Wide Area Network (LoRaWAN) is a wireless communication protocol used in open Radio Frequency (RF) communication links. However, this openness also makes LoRaWAN vulnerable to Denial of Service (DoS) attacks. LoRaWAn DoS attacks can result in increased packet errors, delays, and additional energy costs, posing risks to the reliability and effectiveness of Industry 5.0 automation. To address these threats, this paper proposes a novel evaluation model that combines the entropy weighting method (EWM) with grey relational analysis (GRA). The model focuses on an intelligent healthcare scenario as a representative application of Industry 5.0. It assesses LoRaWAn performance by considering metrics such as Packet Error Rate (PER), latency, and energy consumption.

LoRaWAN is an overwhelmingly popular wide area networking protocol that is capable of deploying city-wide Internet of Things (IoT) networks. Increase on the deployment of LoRaWAN in the last few years has led to exponential increase on the number of LoRa sensory and actuating end devices and results in more congestion in LoRaWAN network traffic. Moreover, the evolving AI-IoT (AIoT) applications (e.g., AI-powered environment monitoring system) create needs for more computing power with low latency requirements. To mitigate the high latency issue and the shortage of computing power due to continuously demanding quality of service (QoS) requirements of IoT applications, the Edge-Cloud server structure has been explored in a thorough manner in research area in recent years. An IEEE 2668 standardized IoT infrastructure system is presented in this work focusing on analyzing the performance of applying Edge-Cloud network server structure to LoRaWAN networks and provide standardized edge computing LoRaWAN infrastructure. This work uses queuing network to quantitively analyze the performance of an edge computing infrastructure applied to LoRaWAN and uses IEEE 2668 to quantitively present the performance and applicability of the Edge-Cloud LoRaWAN infrastructure.

LoRa wide area network (LoRaWAN), an emerging IoT protocol, has been popularized in large-scale applications, given its long-range and low-power properties. Hitherto, there is no appropriate traffic model for LoRaWAN to estimate the heterogeneous arriving traffic at the network server cluster (NSC). Inefficient computation power planning or even processing failure might be further caused. Radio replication, commonly existed in the arriving traffic at NSC in LoRaWAN, also causes difficulty estimating the makespan (i.e., mean processing time in NSC). To overcome the abovementioned limitations, a heterogeneous radio-replication-aware traffic aggregation model is proposed to estimate the arriving traffic for LoRaWAN. In addition, a radio-replication-combined supermarket model (RRC-SM), on top of HTAM, is proposed to achieve load balancing among servers in LoRaWAN. Furthermore, a nondominated sorting genetic algorithm based on multiobjective optimization is developed to simultaneously minimize cost and latency on NSC. Experiments reveal that the proposed HTAM and RRC-SM agree well with the simulation outcome. Under the arriving traffic estimated as 6.16 erlangs with four radio replications of each arriving packet on average, the proposed RRC-SM provides more than 50% reduction on the total processing latency and 75% reduction on the number of servers in NSC than other existing models.

This paper introduces the time synchronization approaches to the Institute of Electrical and Electronics Engineers (IEEE) P1451.0 standard-based sensor networks for Internet of Things (IoT) applications. A time synchronization architecture of IEEE P1451.0 standard-based sensor networks is described including two-level time synchronization systems in IEEE P1451.0 and P1451.1.X standards-based wide-area network (WAN) and IEEE P1451.0 and P1451.5.X standards-based local area networks (LANs). However, this paper mainly focuses on the time synchronization approach of IEEE P1451.0 and P1451.1.6 standards-based WANs and provides two implementations of time synchronization of IEEE P1451.0 and P1451.1.6 using wireline and wireless networks with their preliminary results to verify that the time synchronization approach of IEEE P1451.1.6 functions properly. In addition, the time synchronization transducer electronic data sheets (TEDS) of P1451.1.6 is described.

Internet of Things (IoT) has become one of the most popular technologies in recent years, covering from citywide services to industrial applications, which enlarges the smart life for human beings. Through IoT, billions of IoT end devices can be interconnected to support various applications. The emergence of low-power wide-area network (LPWAN) technologies provides a great opportunity to support such an enormous network with their kilometer-level coverage and uA-level power consumption. To improve the efficiency of network resources of LPWANs, the cooperated IoT is proposed by researchers. However, the current LPWAN consists of diverse protocols, equipment, and design standards, rendering the increasing development effort on designing a compliance network by developers. To address this issue, the IEEE 1451, developed by Instrumentation and Measurement Society, is proposed. The IEEE 1451 standardized the wireless IoT systems with wireless transducer interface module (WTIM), network capable application processor server (NCAP Server) and NCAP Client. Besides, the application programming interfaces (APIs) and transducer electronic data sheet (TEDS) are also standardized. Based on the IEEE 1451, a standardized structure for LPWANs, namely IEEE1451-LPWAN is introduced. In addition, an M/M/1/N based queueing model is built to analyze the queueing performance of IEEE1451-LPWAN, which provides guidance for adopters in the future.

The received signal strength (RSS) finger-print-based approaches are widely used for indoor location-based services (LBSs). The emerging long range wide area network (LoRaWAN) is a cost-effective solution for indoor latency-tolerant LBSs attributed to its long-range property. In general, there are serious RSS fluctuations due to fadings along the communication path, thus significantly jeopardizing the localization accuracy. To overcome the challenge, in this article we propose the extreme RSS (ERSS) to stabilize the fingerprint database and formulate boundary autocorrelation to downsize tremendously the searching complexity and thus proliferating localization accuracy. In essence, the RSS fluctuations are modeled as a Bernoulli random process so that the RSS stability can be estimated by a newly defined fluctuation analytic function. To mitigate the impact of the perturbative fluctuation, the ERSS is further defined to cultivate a highly stable and robust fingerprint database which withstands environmental dynamics. In addition, boundary autocorrelation is developed to measure and compare the similarity between the measured RSS values versus the prestored fingerprint database. RSS values with low autocorrelation coefficients are eradicated from the typically lengthy searching. The downsized complexity significantly improves the localization accuracy. Experiments were carried out and the results revealed that the proposed method achieved sub-10-m localization accuracy in indoor environments. Such accuracy is encouraging and superior in contemporary LoRaWAN measurements.

In recent years, electric vehicles (EVs) have been widely applied to improve environment. The EV could provide environmentally friendly transportation but have the demerit of low battery capacity. Rapid charging by charging stations (CS) is critically needed especially for those drivers in long distance trip. Thus, a routing optimization problem for EVs charging should be addressed. Furthermore, this problem becomes more practical when the EV density is high at peak. In this scenario EVs are only allowed to obtain energy that render them able to arrive at the destination. In this paper, we formulate an emergent EV charging optimization problem in EV high density area which has not been discussed in related work and a novel genetic algorithm based emergent charging scheduling (GECS) scheme is proposed. The genetic algorithm (GA) is presented to simplify the multi-objectives optimization process in this case. Furthermore, incorporation of the Earliest Deadline First (EDF) which indicates the minimum recharging deadline time as the subject and Nearest Job First (NJF) which indicates the minimum recharging path as the subject into genetic optimization process can relieve the charging emergent condition and improve optimized results. The simulation results show that the proposed scheme can provide an optimal solution to minimize the average distance and waiting time for emergent charging in EV high density region.

With the rapid exhaustion of fossil energy, electric vehicles (EVs) become one of the key candidates for the next generation of transportation. Increasingly perfect technology developed makes EVs grow significantly. Therefore, Charging Stations (CSs), as accessories and necessities of EVs, should form a network with optimal planning. Inappropriate CS network design could cause series of negative effects to the popularization of EVs, the layout of the city traffic network and the financial cost of CS network construction, etc. Besides, the charging infrastructure planning for cities with large population and high EV density becomes even difficult. In this paper, an Effective Planning of CSs Network (CSN) is proposed. Comprehensive environmental elements (e.g. cities' and CSs' information, EV charging status, etc.) are considered in CSN. The CSN deals with complicated city planning in giant cities (i.e. large population, high EV density, etc.). Hong Kong is selected as the case study because it can be regarded as a typical giant city. Results show that the proposed CSN can ensure the EVs can find a CS before it is out of power. Besides, the CSN saves ~18% financial cost for the charging infrastructure planning in giant cities.

Due to lack of heart monitoring device, heart problems have been causing more than 17 million people death every year. Recently, researches on IoT (Internet of things) system provide feasible solutions to solve the problems. Such as LoRa wireless communication protocol, it can cover more than 1km2area and reliable communication connection. In heart monitoring system, packet transmission frequency should be considered carefully because of the reliability. Therefore, in this paper, the packet loss of heart monitoring system has been analyzed through packet length, transmission frequency and communication distance. Results shows that the packet loss can be less than 1% through specified communication property. The result in the paper can provide reference for reliable heart monitoring system design.

Smart transportation and smart healthcare are considered as essential Smart City applications. The emerging light-weight sensors facilitate real-time monitoring drivers' status in various applications especially safety and healthcare. As such, the statistics reveals that >60% of adult drivers felt sleepy while driving, and drunk drivers are found in >40% of traffic accidents. In this paper, an electrocardiogram (ECG) based Drivers' Status Monitoring (ECG-DSM) system is developed to detect drowsy and drunk driving. The proposed ECG-DSM extracted similarities of ECG signals under normal, drowsy and drunk conditions, and the corresponding feature vector was built. The classifier is expected to alert drivers accurately and timely to prevent traffic accidents. Hence, the classifier's trade-off between accuracy and detection time was analysed by adjusting the dimensionality of feature vector. Safety analysis using Monte Carlo simulation was carried out to determine the best classifier under practical working environment. The results demonstrated that the best classifier for ECG-DSM achieves 91 % of average accuracy and 4.2s of detection time, and it can prevent >92 % of vehicle collisions due to drowsy and drunk driving. The proposed work will contribute to road traffic safety and save $50 billion US dollars on the cost of traffic injuries.

In a metropolitan city, the power consumption of buildings is a great concern for not only economic but also environmental concerns. Researchers is proposing some new low power wide area (LPWA) IoT communication protocols to monitor and control power consumption in buildings. Three common LPWA communication protocols include: NB-IoT, LoRa and Sigfox, which can provide different functions or performance under different conditions. For building management system, these protocols can create platform to monitor and control the “things”, such as energy. Light Poles are used to be built to continuously lighten up the city which are served as passive devices to be controlled by the Highway Department. With the LWPA communication protocols and sensors or actuators, they can provide a low power low cost network nodes to serve local community; and uplink the data to Cloud via mobile communication network or Ethernet, as Smart Poles. In this paper, some fundamental scheme and based on LPWA protocols to design building management system are introduced; and prototype of Smart Poles have been networked and applied in a traditional industrial area.

Intelligent sensing and actuation in building applications has been considered by many Heating, ventilation and air conditioning (HVAC) experts. Wireless Sensor Network (WSN) performs as an efficient communication tool for human comfort (e.g. indoor thermal control). In this paper, an analysis of Packet Error Rate (PER) in WSN for HVAC system was implemented. Based on the collected PER information, a WSN network was designed and built for achieving low PER. The network provided guidance for large-scale WSN design in HVAC systems.