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Power and energy conservation is an essential issue during the development of wireless sensor networks (WSNs). Hierarchical clustering is one typical method to conserve the power of networks. For mobile sensor networks (MSNs), several clustering approaches have been presented to prolong the network lifetime by considering the sensor mobility factor during the cluster head (CH) selection. However, as mobile sensors possess energy-harvesting functions, the capability to collect power would be a critical factor in the clustering design. In this article, an extended hierarchical clustering method for energy-harvesting mobile WSNs has been proposed. In the presented scheme, the energy-harvesting rate has been considered in the CH selection processes. Simulation results indicate that the proposed approach is able to prolong the network lifetime in the early morning for solar-based energy-harvesting MSNs.

Pedestrian dead reckoning (PDR) is a potential technique for smartphone-based indoor localization using the built-in accelerometers and gyroscopes. However, most current PDR positioning approaches restrict the pose to carry a phone, such as holding it in front of the body during tracking. In addition, heading determination is the primary error sources in PDR systems, and hence, a magnetometer is normally required to reduce heading errors. However, in indoor environments, magnetometer outputs would be seriously distorted by magnetic disturbances from the building structures and electronics. In this paper, an experimental heuristic approach to multi-pose PDR (mpPDR) indoor positioning for structured environments has been proposed. Six poses and four modes to carry a phone could be recognized, and then, on the basis of different modes, an experimental approach to the heading determination without using magnetometers has been presented to reduce the heading error considering the effects of turning and hand-shaking events. The experimental results indicate that the proposed approach supports four smartphone modes with a high position accuracy of 97.99%.

With economic development and changes in the industrial environment in the world, it is necessary to build an automated production line in the modern factory. Because of the excellent functions and high stability of the programmable logic controller (PLC), it is mainly used to integrated control systems to control devices. e.g., sensors, servo motors, and pressure systems. This paper combines PLC, mobile App, and Arduino modules to create a fully automated agricultural technology.

For discrete automation systems, certain human operations may violate desired safety requirements and result in catastrophic failure. For such humanin-the-loop systems, this paper proposes a systematic approach to developing supervisory agents which guarantee that manual operations meet required safety specifications. In the present approach, Petri nets (PN) are applied to construct a system model and synthesize a desired supervisor. Applications to 1) a rapid thermal process (RTP) in semiconductor manufacturing controlled over the Internet (Lee and Hsu, 2003) and 2) a two-robot remote surveillance system (Lee et al., 2005) are provided to demonstrate the practicability of the developed supervisory control approach. The technique developed in this paper is significant in industrial applications. 1.1 General Review Basically, an automated process is inhe rently a discrete event system (DES). The Petri net (PN) has been developed as a powerful tool for modelling, analysis, simulation, and control of DES. PN was named after Carl A. Petri (1962), who created a net-like mathematical tool for describing relations between the conditions and the events. PN was further developed to meet the need in specifying process synchronization, asynchronous events, concurrent operations, and conflicts or resource sharing for a variety of industrial automated systems at the discrete-event level. Starting in the late of 1970’s, researchers investigated possible industrial applications of PN in discrete-event systems as in the survey/tutorial papers of Murata (1989), Zurawski and Zhou (1994), David and Alla (1994), and Zhou and Jeng (1998).

With the increasing attention to sustainability, several studies have attempted to develop human-electric bikes which provide the power to assist the human rider from an electric motor when the rider is pedalling. For such systems, the design of the power-assisted controller plays a critical role to ensure the comfort and safety of the rider. In practical situations, a bike may be utilised by multiple riders such as the users of bike-sharing systems. However, the influence of different human riders is seldom discussed in the power-assisted controller design. In this study, an enhanced fuzzy-logic-based control approach with a user-adaptive mechanism has been presented to online adjust the fuzzy parameters for power-assisted regulation so as to ensure the riding comfort and safety. Simulation results display that the proposed user-adaptive approach improves the comfortability and safety for the riding in urban areas. It is believed that the techniques presented in this study could further be adopted in public bike-sharing systems for short-range city commuters.

Energy management in wireless sensor networks is an important issue for the Internet of Things applications. Transmission power control (TPC) is one of the approaches to conserve energy in sensor networks. However, most existing TPC methods assume sensor nodes are stationary after deployment and thus do not support mobile sensing environments. In this paper, a predictive TPC approach, namely grey-fuzzy-logic-based TPC (grey-FTPC), has been proposed for mobile sensor networks using grey prediction and fuzzy inference systems. Simulation results indicate that the proposed approach not only reduces the energy consumption, but also maintains a proper packet delivery ratio (PDR) for mobile sensing environments. On average, the proposed grey-FTPC achieves 92.3% of the PDR of the conventional maximum transmission energy (MTE) approach, but consumes only 57.4% of the transmission energy of the MTE. Moreover, the grey-FTPC approach has an approximate performance compared with the Markov-based TPC, but does not require exhaustive experimental data to build models. Hence, it is believed that the proposed grey-FTPC approach could further be applied to highly mobile sensing environments.

Topology control in wireless sensor networks (WSNs) balances the communication load on sensor devices and increases the network lifetime and scalability. Hierarchical or cluster-based design is one of the approaches to conserve the energy of the sensor networks in which the nodes with the higher residual energy could be used to gather data and route the information. However, most of the previous work on clustering has adopted a two-layer hierarchy, and only few methods studied a three-layer scheme instead. Based on a three-layer hierarchy, this paper has proposed a semi-distributed clustering approach by considering a hybrid of centralized gridding for the upper level head selection and distributed clustering for the lower level head selection. The simulation results show that the proposed approach is more efficient than other distributed algorithms. Therefore, the technique presented in this paper could be further applied to large-scale WSNs.

Recently, due to the increasing demand on custom-made soft drink, this paper has developed an automatic drink making system by using a networked programmable logic controller (PLC) and Java applet. In the present scheme, a Java-based and cross-platform applet is designed for users to send customized order from a smartphone (or PC) to the PLC through Internet communication. Moreover, a simplified PLC-controlled drink making mechanism is implemented to produce the custom-made drinks. Finally, several application cases are provided to demonstrate the feasibility and practicality of the developed system.

The Internet of Things is being established nowadays, and the deployment of devices to be interconnected with each other and to the Internet is becoming a more common issue. The Internet of Things is structured in several levels and, in this regard, depending on the layer in which these devices are located, the complexity range and specific constraints arise. In the lowest level of this structure, the so-called edge is found, where the data are gathered from the environment by tiny electronic devices which are very limited in energy, computing, and memory resources. These devices, in turn, present different levels of complexity, which lead to a distinction between the edge layer and the sensor or extreme edge layer. In the extreme edge is where the most essential and limited tasks are carried out, these are sensing and sending data. Meanwhile on the edge, in addition to sensing, some processing can be performed in order to offload upper layers and to save precious energy by not communicating useless data. In this review paper, the structure of the Internet of Things is presented and the extreme edge is detailed, presenting the implementation options and requirements, with the purpose of having a better understanding of the needs when a specific application has to be developed and a set of devices has to be deployed. A special emphasis receives the bottom layer, focusing on devices oriented to last unattended for tens of years.

Recently, due to the increase of environmental awareness, air quality has attracted much more attention. In this paper, an indoor air quality supervision system using ZigBee wireless networks has been proposed. The developed system provides a simple way to monitor and control the indoor air quality (IAQ) for residential building applications. In this present scheme, several sensors are employed to detect a variety of gases, such as carbon monoxide (CO), carbon dioxide (CO2), as well as the fine particulate matter (PM2.5). In addition, by using the developed user interface APP, people could observe the real-time status anytime and anywhere.

In recent years, energy conservation has become a critical issue. Residential lighting consumes a surprisingly large share of the electricity. In this paper, a residential lighting control system using ZigBee wireless technology has been proposed. In the present scheme, the ZigBee localization technique is integrated into the lighting control system so as to reduce the power consumption. The experimental results demonstrate the feasibility of the proposed approach that could save the energy around 11.81%.

This paper presents a preliminary development of the smart shopping cart (SSC) that can be integrated into the smart mall system. The SSC can provide customers with the efficient user interface so that the shopping service can be effectively promoted. In the current design, with the function of face recognition on the user interface, the SSC can recognize the customer and further provide the associated assistive shopping information based on the purchase history. With the use of radio-frequency identification (RFID) tags, the SSC can automatically detect the various products which are being added in the cart and show the related information on the user interface. Through the searching function of SSC, the purchasing efficiency and navigation aid in the mall can be effectively supplied. Finally, the automatic billing service can be done by the SSC and the stored shopping data will be transmitted to the cloud server of shopping mall. The experimental demonstration shows the effectiveness of the proposed SSC which interacts with the customer and provides efficient shopping service.

Control design plays a key role in electric-assist bikes. This paper has established dynamic models of electrically assisted biking systems, and then, designed proportion-assisted power controllers (PAPC) in accordance with Taiwan government rules. In the PAPC controllers, current bike speed and pedal torque are used as inputs to determine the assisted torque generated from a motor. On the other hand, a fuzzy logic controller (FLC) has been also designed, using the current bike speed and pedal frequency as inputs to determine the assisted torque. In order to compare these two controllers, simulations of riding bikes on a flat ground and different slopes have been performed. Simulation results show that the FLC outperforms PAPC in a more stable bike speed.

In order to collect information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Clustering provides an effective way to prolong the lifetime of WSNs. Current clustering approaches often use two methods: selecting cluster heads with more residual energy, and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, most of the previous algorithms have not considered the expected residual energy, which is the predicated remaining energy for being selected as a cluster head and running a round. In this paper, a fuzzy-logic-based clustering approach with an extension to the energy predication has been proposed to prolong the lifetime of WSNs by evenly distributing the workload. The simulation results show that the proposed approach is more efficient than other distributed algorithms. It is believed that the technique presented in this paper could be further applied to large-scale wireless sensor networks.

This paper was motivated by the requirement of remote coordination for flexible manufacturing systems (FMS), in which certain requested commands may lead to undesired states. For such discrete event systems (DES), this paper applies a command filtering scheme for modeling and synthesis of filters using Petri nets so as to guarantee that the closed coordinated manufacturing system satisfies the requirements. Moreover, a systematic algorithm for the design and integration of modular command filters is proposed in order to cope with the complexity and realization issues in large-scale FMS. To show the practicability of the developed method, an application to an FMS with three product types is provided. The proposed approach contributes a promising tool for preventing undesirable actions from occurring in FMS which may be also applied to other types of DES if appropriately modified.

Recently, modeling and simulation of hybrid dynamic systems (HDSs) have attracted much attention. However, since simultaneously dealing with the discrete and continuous variables is very difficult, most of the models result in a unified but more complicated and unnatural format. Moreover, design engineers cannot be allowed to use their preferred domain models. Based on the multiparadigm modeling concept, this correspondence proposes a Petri net framework with associated state equations to model the HDSs. In the presented approach, modeling schemes of the hybrid systems are separated but combined in a hierarchical way through specified interfaces. Designers can still work in their familiar domain-specific modeling paradigms, and the heterogeneity is hidden when composing large systems. An application to a rapid thermal process in semiconductor manufacturing is provided to demonstrate the practicability of the developed approach.