Outlier detection strategies for WSNs: A survey

The main purpose of the study is to review the evolution of wireless sensor network security and routing techniques. Recent years have seen tremendous growth in Wireless Sensor Networks (WSNs). As WSN's become more and more crucial to everyday life, their security and trust become a primary concern. However because of the nature of WSNs, security design can be challenging. Trust-aware routing protocols play a vital role in security of Wireless Sensor Networks (WSNs). The review study provides an overview of Wireless Sensor Network (WSN) and discusses security issues and the routing techniques for high quality of service and efficient performance in a WSN. In order to identify gaps and propose research directions in WSN security and routing techniques, the study surveys the existing body of literature in this area. The main focus is on trust concepts and trust based approaches for wireless sensor networks. The study also highlights the difference between trust and security in the context of WSNs. The trust and security are interchangeable with each other when we elaborate a secure system and not same. Various surveys conducted about trust and reputation systems in ad hoc and sensor networks are studied and compared. Finally we summarize the different trust aware routing schemes.

A survey of wireless sensor network security and routing techniques

Wireless Sensor Networks (WSN) differ from traditional wireless communication networks in several characteristics. One of them is the power awareness since the batteries of sensor nodes have a restricted lifetime and are difficult to be replaced. Therefore, all protocols must be designed to minimize energy consumption and to preserve the longevity of the network. Routing protocols in WSN aim at accomplishing power conservation. Most of researches have focused on energy efficient solutions regardless of the communication between Cluster Heads (CH) and Base Station (BS). When the sensor field is far away from the BS, the CH are burdened with heavier relay traffic and tend to die much faster. To solve this problem, a Multi-hop Energy Efficient routing protocol based on Data Controlling (MEEDC) is proposed in this paper. Our work focuses on (i) a heterogeneous network and (ii) a sensitive data controlling. The role of super nodes in the proposed heterogeneous network is to connect the CH and the BS. They are responsible for transmitting packets received from the CH to the BS, thus the CH can preserve some energy in data forwarding. The control of data transmission tries to reduce the number of transmissions and thus considerable energy conservation is achieved. Simulation results show that the MEEDC protocol significantly prolongs the network survival time.

Multi-hop Energy Efficient routing protocol based on Data Controlling for Wireless Sensor Networks

This review presents the state of the art and a global overview of research challenges of real-time distributed activity recognition in the field of healthcare. Offline activity recognition is discussed as a starting point to establish the useful concepts of the field, such as sensor types, activity labeling and feature extraction, outlier detection, and machine learning. New challenges and obstacles brought on by real-time centralized activity recognition such as communication, real-time activity labeling, cloud and local approaches, and real-time machine learning in a streaming context are then discussed. Finally, real-time distributed activity recognition is covered through existing implementations in the scientific literature, and six main angles of optimization are defined: Processing, memory, communication, energy, time, and accuracy. This survey is addressed to any reader interested in the development of distributed artificial intelligence as well activity recognition, regardless of their level of expertise.

https://www.mdpi.com/1424-8220/21/8/2786/pdf

From Offline to Real-Time Distributed Activity Recognition in Wireless Sensor Networks for Healthcare: A Review.

Hybrid outlier detection (HOD) method in sensor data for human activity classification

 Abstract— Wireless Sensor Networks (WSN) consist of small nodes with sensing, computation, and wireless communications capabilities. Sensor networks are "data-centric" networks and are application specific. Adjacent nodes may have similar data and there is a need for communication between nodes about the data to be sent. Thus, energy-efficient routing algorithms suitable to the inherent characteristics of these types of networks are needed. Also, to prolong the lifetime of the sensor nodes and to communicate each other designing efficient routing protocol is critical. This paper makes an energy and lifetime comparison of flat and hierarchical routing protocols. Simulation is performed using Matlab. This analysis reveals the important features that need to be taken into consideration while designing and evaluating new routing protocols. In flat routing Protocols all nodes participate equally in the network. But in Hierarchical routing techniques, cluster heads are formed to transmit data to the Base station. So, energy consumption is less in hierarchical routing protocols compared to flat routing protocols.

http://ijarece.org/wp-content/uploads/2013/08/IJARECE-VOL-1-ISSUE-3-61-67.pdf

Comparative Analysis on Routing Techniques in Wireless Sensor Networks

On streets and highways, traffic signs have a specific set of characteristics that may be used to distinguish one from another. A real-time traffic sign recognition and identification process based on neural networks. A quicker R-CNN technique is utilised to recognise traffic signals, and a convolutional neural network is employed to categorise them using the Inception V2 architecture. Some elements, such as light, occlusion, blurring, and others, might make it difficult. This proposed work could be used in a variety of fields, including the Advanced Driving Assistant System and self-driving automobiles. The classification network is used to execute particular classification tasks before computing the bounding box regression. The tests are carried out using a standard benchmark dataset, and the results indicate that the approach is both successful and resilient.

G. Nivetha

Papers

Hybrid outlier detection (HOD) method in sensor data for human activity classification

Comparative Analysis on Routing Techniques in Wireless Sensor Networks

Traffic Sign Prediction and Classification Using Image Processing Techniques