A Review on Conservation of Energy in Wireless Sensor Networks

This paper is a review on energy conservation in wireless sensor networks (WSNs). Due to the nature of wireless sensor nodes in terms of deployment and their common usage in terrains with limited access, recharging or replacing sensor nodes batteries may be difficult. This paper examined various sources of energy in WSNs Battery, energy harvesting and energy transference. Also, various energy usage operations and energy wastage activities in WSNs were examined, and comparisons of different routing protocols based on network structure, energy dissipation, data communication cost, and entire energy usage in WSNs were itemized. The prospects of the machine learning (ML) approach in addressing energy constraint issues in WSNs were reviewed. This paper recommends a compound approach in routing decisions to maximize energy usage operation and minimize energy wastage activities, consideration for energy harvesting and transference mechanisms, and exploring the potentials in ML algorithms to resolve energy problem in wireless sensor networks.

A Survey of Mobile Ticketing Services in Urban Mobility Systems

Modern mobile ticketing service solutions facilitate access to mobility services and free customers from difficult purchasing decisions. However, implementing these solutions is complex, as they involve many different stakeholders, with sometimes conflicting interests. This paper presents a survey of mobile ticketing services in the urban mobility context. It starts by defining mobile ticketing and explores the different electronic ticket schemes that are being implemented around the world, as well as the most used technologies to provide the service. Then, it addresses the complex mobile ticketing ecosystem, identifying the main actors involved, their motivations, and concerns. This allows the authors to define their role and contribution to the mobile ticketing ecosystem. Finally, the paper presents future trends and research directions related to mobile ticketing services, being a valuable guide for researchers and practitioners.

GuideMe

The interest for indoor navigational systems is expanding daily with concerns among visually impaired people who cannot navigate safely indoors. The main goal of such systems is the localization and direction of the individual who has a wearable device that provides voice commands to navigate indoor buildings. This paper aims to present the design and the implementation of the GuideMe project. The GuideMe project's goal is the design, implementation, and evaluation of a navigation system focused on people who face troubles in indoor moving utilizing a wearable device. Specifically, the focus group is people suffering from visual impairment. The person carrying the wearable device takes guidelines about the location from indoor ultrawide band (UWB) anchors. The commands provided are about indoor direction through voice commands, assisting him to avoid obstacles in his route. The authors present the architecture and the details of the various modules, which consist of the proposed indoor navigation system, and some initial evaluations of the proposed system yielding promising results.

Large-Scale Software-Defined IoT Platform for Provisioning IoT Services on Demand

Internet of things (IoT) has developed into an interconnected platform infrastructure for providing everyday services. Emerging end-to-end IoT services are being developed for local and multiple distributed regions. To realize the on-demand services in a timely and economically beneficial way, programmability and reusability are crucial for provisioning and reusing IoT resources. Existing IoT platforms are rigid and cannot be easily adapted to accommodate new services. This paper proposes a programmable large-scale software-defined IoT model for provisioning IoT services on demand with two levels of management and orchestration. One orchestrates services over geographically distributed clusters and the other orchestrates services over IoT devices within a cluster. The model entails the design of IoT-specific controllers, software-defined virtual sensors, and a new protocol for managing resource-constrained but enriched devices. The model allows provisioning and resource-sharing of end-to-end IoT services on demand. Implementation results demonstrate the feasibility and efficiency of the proposed model.

A Power Control Strategy for IoT Sensors Developed for 5G Networks

This research work presents a power control mechanism developed for ProSe-enabled sensors so that the sensors can be smoothly integrated into the fifth generation (5G) of mobile networks. It is strongly anticipated that 5G networks will provide an enabling environment for the 21st century innovations like the internet of things (IoT). Sensors are pivotal in IoT. The proposed power control mechanism involves an open loop power control (OLPC) mechanism that a ProSe-enabled sensor has to use to establish communication with a base station (BS) and a closed loop power control (CLPC) the BS then has use to establish transmit power levels for devices to be involved in a device to device (D2D) communication depending on the prevailing channel conditions. The results obtained demonstrate that the developed scheme does not adversely affect the quality of service (QoS) of a 5G mobile network.

Optimization of C5.0 Classifier With Bayesian Theory for Food Traceability Management Using Internet of Things

In order to survive with the existing financial circumstances and the development of global food supply chain, the authors propose efficient food traceability techniques using the internet of things and obtain a solution for data prediction. The purpose of the food traceability is used to retain the good quality of raw material supply, diminish the loss, and reduce system complexity. The primary issue is to tackle current limitations to prevent food defects from exceeding hazardous levels and to inform the safety measures to the customers. The proposed hybrid algorithm is for food traceability to make accurate predictions and enhanced period data. The operation of the internet of things is addressed to track and trace the food quality to check the data acquired from manufacturers and consumers. The experimental analysis depicts that proposed algorithm has high accuracy rate, less execution time and error rate.