Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

Energy consumption model and energy efficiency of machine tools: a comprehensive literature review

While the Internet of Things (IoT) is driving a transformation of current society toward a smarter one, new challenges and opportunities have arisen to accommodate the demands of IoT development. Low power wireless devices are, undoubtedly, the most viable solution for diverse IoT use cases. Among such devices, Bluetooth low energy (BLE) beacons have emerged as one of the most promising due to the ubiquity of Bluetooth-compatible devices, such as iPhones and Android smartphones. However, for BLE beacons to continue penetrating the IoT ecosystem in a holistic manner, interdisciplinary research is needed to ensure seamless integration. This paper consolidates the information on the state-of-the-art BLE beacon, from its application and deployment cases, hardware requirements, and casing design to its software and protocol design, and it delivers a timely review of the related research challenges. In particular, the BLE beacon’s cutting-edge applications, the interoperability between packet profiles, the reliability of its signal detection and distance estimation methods, the sustainability of its low energy, and its deployment constraints are discussed to identify research opportunities and directions.

BLE Beacons for Internet of Things Applications: Survey, Challenges, and Opportunities

The present electric power system structure has lasted for decades; it is still partially proprietary, energy-inefficient, physically and virtually (or cyber) insecure, as well as prone to power transmission congestion and consequent failures. Recent efforts in building a smart grid system have focused on addressing the problems of global warming effects, rising energy-hungry demands, and risks of peak loads. One of the major goals of the new system is to effectively regulate energy usage by utilizing the backbone of the prospectively deployed Automatic Meter Reading (AMR), Advanced Meter Infrastructure (AMI), and Demand Response (DR) programs via the advanced distribution automation and dynamic pricing models. The function of the power grid is no longer a system that only supplies energy to end users, but also allows consumers to contribute their clean energy back to the grid in the future. In the meantime, communications networks in the electric power infrastructure enact critical roles. Intelligent automation proposed in smart grid projects include the Supervisory Control And Data Acquisition/Energy Management Systems (SCADA/EMS) and Phasor Management Units (PMU) in transmission networks, as well as the AMR/AMI associated with field/neighborhood area networks (FAN/NAN) and home area networks (HAN) at the distribution and end-use levels. This article provides an overview of the essentials of the progressive smart grid paradigm and integration of different communications technologies for the legacy power system. Additionally, foreseeable issues and challenges in designing communications networks for the smart grid system are also rigorously deliberated in this paper.

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The Progressive Smart Grid System from Both Power and Communications Aspects

In recent years there has been several technological advances in Wireless Sensor Networks (WSN), but energy still remains a paramount resource. The amount of available energy has a direct effect on the performance, functionality and lifetime of WSN. Being bound by cost and size, sensor nodes are usually equipped with limited amount of energy and therefore requires a replacement of batteries occasionally. But replacement might not always be feasible option and in some scenarios might even be prohibitive. This indicates the need for more viable solutions, these involve generating energy at the sensor nodes or have it delivered to them i.e., energy harvesting or wireless energy transfer. The objective of this paper is threefold: first we present a survey on potential renewable energy resources along with their characteristics and applications in WSN. Second, this study also describes various battery recharging techniques and their applications with respect to WSN. Finally, we discuss formidable issues, challenges and future research directions.

Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: A review

In recent years, the home environment has seen a rapid introduction of network enabled digital technology. This technology offers new and exciting opportunities to increase the connectivity of devices within the home for the purpose of home automation. Moreover, with the rapid expansion of the Internet, there is the added potential for the remote control and monitoring of such network enabled devices. However, the adoption of home automation systems has been slow. This paper identifies the reasons for this slow adoption and evaluates the potential of ZigBee for addressing these problems through the design and implementation of a flexible home automation architecture. A ZigBee based home automation system and Wi-Fi network are integrated through a common home gateway. The home gateway provides network interoperability, a simple and flexible user interface, and remote access to the system. A dedicated virtual home is implemented to cater for the system's security and safety needs. To demonstrate the feasibility and effectiveness of the proposed system, four devices, a light switch, radiator valve, safety sensor and ZigBee remote control have been developed and evaluated with the home automation system.

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A zigbee-based home automation system

Because of the recent developments in both wireless technologies and low power electronics, wireless devices consume less and less power and are promising the possibility to operate continuously by using energy harvesting technologies. The interest in Wireless Sensor Networks (WSNs), powered by environment energy harvesters, has been increasing over the last decade, especially those using thermal energy harvesting. In this paper, a low temperature thermal energy harvesting system, which can harvest heat energy from a temperature gradient and convert it into electrical energy, which can be used to power wireless electronics, is proposed. A prototype based on three subsystems is presented to extract heat energy from a radiator and use it to power ZigBee electronics. High efficiency and a long system lifetime are two of the main advantages of this design. The experimental results show that a maximum of 150mW power can be harvested by the prototype and the system can continue to operate normally when the harvesting voltage is as low as 0.45V. Theoretical calculations suggest that by placing the two AA batteries by proposed thermal energy harvesting system, a ZigBee Wireless Radiator Valve can operate for more than eight years.

Xin Lu

Papers

A zigbee-based home automation system

Thermal energy harvesting for WSNs

A systematic approach of process planning and scheduling optimization for sustainable machining

Cyber Physical System and Big Data enabled energy efficient machining optimisation

Fog Computing and Convolutional Neural Network Enabled Prognosis for Machining Process Optimization