The book "The Fundamentals and Empirical Design of a Smart Fire Detection System"

The book entitled "The Fundamentals and Empirical Design of a Smart Fire Detection System" was published by Cambridge Scholars Publishing in November 2020. This book introduces a smart fire detection system designed using a wireless sensor network and fuzzy methods. This system predicts, controls, and provides alerts to various events based on intelligent techniques. Routing protocols are performed based on intelligent procedures in which they are classified into two main groups: static and dynamic. Static protocols are used to transmit data packets between stationary nodes, while dynamic protocols are applied to transmit messages between rescue teams and fire departments. The active and passive states are specified for sensor nodes to balance the remaining energy of the nodes and prolong the network lifetime. The probability of explosion, fire, burn, and suffocation is determined based on fuzzy procedures. People affected can be guided to the exit at event places based on an intelligent method. In addition, members and dispatch routes of rescue and support teams are selected using intelligent methods to reduce financial losses and human casualties. The book will be useful for professors, researchers, and engineers in computer and electrical engineering.

You can obtain more information about this book via the link.

The paper "An Intelligent and Knowledge-based Overlapping Clustering Protocol for Wireless Sensor Networks"

The paper "An Intelligent and Knowledge-based Overlapping Clustering Protocol for Wireless Sensor Networks" was published by Wiley Online Library in International Journal of Communication Systems on July 10, 2018. It proposes an intelligent and knowledge‐based overlapping clustering protocol for wireless sensor networks, called IKOCP. This protocol uses some of the intelligent and knowledge‐based systems to construct a robust overlapping strategy for sensor networks. The overall network is partitioned to several regions by a proposed multicriteria decision‐making controller to monitor both small‐scale and large‐scale areas. Each region is managed by a sink, where the whole network is managed by a base station. The sensor nodes are categorized by various clusters using the low‐energy adaptive clustering hierarchy (LEACH)‐improved protocol in a way that the value of p is defined by a proposed support vector machine–based mechanism. A proposed fuzzy system determines that noncluster heads associate with several clusters in order to manage overlapping conditions over the network. Cluster heads are changed into clusters in a period by a suggested utility function. Since network lifetime should be prolonged and network traffic should be alleviated, a data aggregation mechanism is proposed to transmit only crucial data packets from cluster heads to sinks. Cluster heads apply a weighted criteria matrix to perform an inner‐cluster routing for transmitting data packets to sinks. Simulation results demonstrate that the proposed protocol surpasses the existing methods in terms of the number of alive nodes, network lifetime, average time to recover, dead time of first node, and dead time of last node.

You can find more information about this paper via the link.

The paper "Sensory Life in Sensory World"

The paper "Sensory Life in Sensory World" was published by i-manager Publications in i-manager's Journal on Wireless Communication Networks on July 2017. It describes various physical features and key usages of the popular sensors. Furthermore, three major applications of wireless sensor networks in monitoring, healthcare, and military are mentioned in the paper. Since sensor localization and data mining are two important topics in sensor networks, their categories and characteristics are addressed too. Besides, some of the existing simulators are compared to each other.

You can read information of this paper via the link.

The paper "SMIER: An SVM and MCDA Based, Intelligent Approach for Enhanced Reliability in Wireless Sensor Networks"

The paper "SMIER: An SVM and MCDA Based, Intelligent Approach for Enhanced Reliability in Wireless Sensor Networks" was published by i-manager Publications in i-manager's Journal on Communication Engineering and Systems on September 28, 2017. It proposes an SVM and MCDA based, intelligent approach for enhanced reliability in WSNs, called SMIER. It is considered for a cluster-based sensor network in a way that every Cluster-Head (CH) selects one of its Non Cluster-Head (NCH) nodes as a backup node in a period of time. Initially, the suggested SVM algorithm determines failure probability of each NCH node based on number of events and average distance to events. Afterward, the suggested MCDA controller calculates success rate of the NCH node by using three parameters, including remaining energy, distance, and failure probability. Simulation results show that the proposed approach surpasses some of the existing works in terms of packet delivery ratio, number of alive nodes, and average remaining energy.

You can find more information about this paper via the link.

The paper "A Routing Protocol for Data Transferring in Wireless Sensor Networks Using Predictive Fuzzy Inference System and Neural Node"

The paper "A Routing Protocol for Data Transferring in Wireless Sensor Networks Using Predictive Fuzzy Inference System and Neural Node" was published by Old City Publishing in Ad Hoc & Sensor Wireless Networks, in September 2017. It proposes a new fuzzy-neural based routing protocol, called Routing Protocol using Fuzzy system and Neural node, RPFN. Data packets are transferred from sensor nodes to a desired base station by hop-to-hop delivery. When a sensor node has a new sensed data or a data packet has been received from its neighbors, it selects an appropriate neighbor called candidate node by a fuzzy inference system and a neural node. The proposed Perceptron-based neural node uses four essential parameters including remaining energy, distance to the base station, available buffer, and link quality to choose the best candidate node according to local information. Moreover, parameter “link quality” is determined by the proposed fuzzy system based on distance to neighbor node and response rate. Simulation results demonstrate that RPFN surpasses some existing routing protocols in terms of packet delivery ratio and network lifetime.

You can get more information about this paper via the link.