The expected widespread usage of Internet-of-Things (IoT) devices and the associated diversity of applications will place extra pressure on network resources including bandwidth availability. In networking within IoT, spectrum scarcity requires the consideration of the adaptive cognitive radio (CR) technology to achieve interference-free and on-demand IoT solutions for a number of applications. However, CR networks share the same security weaknesses of legacy wireless networks. Jamming is considered a common attack, where jammers can attack networks in a proactive or reactive approach. In this paper, we study the channel assignment problem under both proactive and reactive jamming attacks. Specifically, we propose a novel probabilistic-based channel assignment mechanism that aims at minimizing the invalidity ratio of CR packet transmissions subject to delay constraints. The proposed scheme exploits the statistical information of licensed primary users activities, fading conditions and jamming attacks over idle channels to provide communicating CR IoT devices with the most secured channels of lowest invalidity ratios. Simulation results show that our proposed security, availability, and quality-aware channel assignment algorithm can significantly improve network performance.

Spectrum Assignment in Cognitive Radio Networks for Internet-of-Things Delay-Sensitive Applications Under Jamming Attacks

With the growing number of mobile devices receiving daily notifications, it is necessary to manage the variety of information produced. New smart devices are developed every day with the ability to generate, send, and display messages about their status, data, and information about other devices. Consequently, the number of notifications received by a user is increasing and their tolerance may decrease in a short time. With this, it is necessary to develop a management system and notification controls. In this context, this work proposes a notification and alert management system called PRISER. Its focus is on user profiles and environments, applying data privacy criteria.

https://www.mdpi.com/1424-8220/19/14/3098/pdf

PRISER: Managing Notification in Multiples Devices with Data Privacy Support.

This work introduces ComfOnt, a semantic framework developed within the context of ambient assisted living, context awareness, and ambient intelligence Italian research projects. ComfOnt leverages knowledge regarding Smart Home inhabitants and their particular needs, the devices deployed inside the domestic environment (appliances, sensors, and actuators), the amount of their energy consumption, and indoor comfort metrics to provide dwellers with customized services. Developed reusing widely adopted ontologies, ComfOnt aims at providing inhabitants with the possibility of having personalized indoor comfort in their living environments and at helping them in scheduling their daily activities requiring appliances; in fact, the proposed semantic framework enables the representation of appliances’ energy consumption and the energy profile of the Smart Home, thus assisting the dwellers in avoiding power cuts and fostering energy savings. ComfOnt serves as a knowledge base for a prototypical application (DECAM) dedicated to Smart Home inhabitants; the architecture and the functionalities of DECAM are here presented.

ComfOnt: A Semantic Framework for Indoor Comfort and Energy Saving In Smart Homes

This project was made possible by UREP grant # UREP19-017-2-007 and by NPRP grant NPRP(10-1203-160008)from the Qatar National Research Fund (a member of Qatar Foundation).

https://onlinelibrary.wiley.com/doi/pdf/10.1002/ese3.361

Design and realization of an open‐source and modular smart meter

Reducing energy consumption in building is an important motivation for building energy monitoring and management system. In this work we focus on AC current measurement for small to large appliances such as air conditioners. Today's market has many low-cost AC current sensors that use different technologies and come with different usage convenience. This paper aims to compare AC current measurement accuracy for four low-cost current sensors in nowadays market. They are ACS712, WCS1800, SCT013, and PZEM004T. We also discuss about their price and difficulty of installation. We use ESP32 wifi-microcontroller to process measurements. We perform the test using AC loads in small steps from zero up to 20 A. Our results show that PZEM004T gives the best performance among these sensors. However, ACS712 is the best value current sensor because of its low price and performance, although it is more difficult on installation.

Accuracy Comparison of Present Low-cost Current Sensors for Building Energy Monitoring

Energy monitoring and conservation holds prime importance in today's world because of the imbalance between power generation and demand. The current scenario says that the power generated, which is primarily contributed by fossil fuels may get exhausted within the next 20 years. Currently, there are very accurate electronic energy monitoring systems available in the market. Most of these monitor the power consumed in a domestic household, in case of residential applications. Many a times, consumers are dissatisfied with the power bill as it does not show the power consumed at the device level. This paper presents the design and implementation of an energy meter using Arduino microcontroller which can be used to measure the power consumed by any individual electrical appliance. Internet of Things (IoT) is an emerging field and IoT based devices have created a revolution in electronics and IT. The main intention of the proposed energy meter is to monitor the power consumption at the device level, upload it to the server and establish remote control of any appliance. The energy monitoring system precisely calculates the power consumed by various electrical devices and displays it through a home energy monitoring website. The advantage of this device is that a user can understand the power consumed by any electrical appliance from the website and can take further steps to control them and thus help in energy conservation. Further on, the users can monitor the power consumption as well as the bill on daily basis.

Implementation of an energy monitoring and control device based on IoT

The emergence of Electric Vehicles (EVs) is a turning point in decarbonizing the road transport sector. In spite of the various apprehensions of the customers, such as range anxiety, long charging times, higher costs, and the lack of charging infrastructures, EVs have managed to considerably penetrate into the market. Appreciable subsidies in EV purchase and possibilities of renewable energy-based local charging equipment have encouraged more and more people to own EVs. Electrifying road transport also calls for scaling up of all stages of the supply chain as it involves a lot of raw materials and critical metals used for battery technology. One of the most important factors determining the range of an EV is the energy density of the battery, which has reached over 300 Wh/kg, from 100-150 Wh/kg a decade ago. This clearly means that the same vehicle can travel double the distance with the same mass. Understanding and modeling the energy consumption in an EV is quintessential in alleviating the fear of range anxiety. This paper presents a detailed mathematical equation-based energy consumption analysis of a particular EV model for Indian roads. Very few researchers have worked on drive cycles suitable for India. The novelty of the current work is that the energy consumption calculation can be worked out for any EV model or vehicle type through simple mathematical equations.

/pdf/energy-consumption-analysis-for-the-prediction-of-battery-3nzhd0we.pdf

Keerthi Unni

Papers

Implementation of an energy monitoring and control device based on IoT

Energy Consumption Analysis for the Prediction of Battery Residual Energy in Electric Vehicles