scholarly journals The Smart Meter Challenge: Feasibility of Autonomous Indoor IoT Devices Depending on Its Energy Harvesting Source and IoT Wireless Technology

Sensors ◽  
2021 ◽  
Vol 21 (22) ◽  
pp. 7433
Author(s):  
Edgar Saavedra ◽  
Laura Mascaraque ◽  
Gonzalo Calderon ◽  
Guillermo del Campo ◽  
Asuncion Santamaria
Keyword(s):  
Energy Consumption ◽  
Energy Harvesting ◽  
Wireless Technology ◽  
Smart Meters ◽  
Wireless Technologies ◽  
Service Interruption ◽  
Communication Processes ◽  
Qualified Personnel ◽  
Iot Devices ◽  
Application Requirements

Most smart meters are connected and powered by the electric mains, requiring the service interruption and qualified personnel for their installation. Wireless technologies and energy harvesting techniques have been proved as alternatives for communications and power supply, respectively. In this work, we analyse the energy consumption of the most used IoT wireless technologies nowadays: Sigfox, LoRaWAN, NB-IoT, Wi-Fi, BLE. Smart meters’ energy consumption accounts for metering, standby and communication processes. Experimental measurements show that communication consumption may vary upon the specific characteristics of each wireless communication technology—payload, connection establishment, transmission time. Results show that the selection of a specific technology will depend on the application requirements (message payload, metering period) and location constraints (communication range, infrastructure availability). Besides, we compare the performance of the most suitable energy harvesting (EH) techniques for smart meters: photovoltaic (PV), radiofrequency (RF) and magnetic induction (MIEH). Thus, EH technique selection will depend on the availability of each source at the smart meter’s location. The most appropriate combination of IoT wireless technology and EH technique must be selected accordingly to the very use case requirements and constraints.

scholarly journals A Comprehensive Review on Energy Harvesting Integration in IoT Systems from MAC Layer Perspective: Challenges and Opportunities

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3097
Author(s):  
Golshan Famitafreshi ◽  
M. Shahwaiz Afaqui ◽  
Joan Melià-Seguí
Keyword(s):  
Energy Consumption ◽  
Energy Harvesting ◽  
Energy Requirements ◽  
Mac Layer ◽  
Unified Framework ◽  
Essential Information ◽  
Survey Paper ◽  
Hybrid Approaches ◽  
Smart Healthcare ◽  
Iot Devices

The Internet of Things (IoT) is revolutionizing technology in a wide variety of areas, from smart healthcare to smart transportation. Due to the increasing trend in the number of IoT devices and their different levels of energy requirements, one of the significant concerns in IoT implementations is powering up the IoT devices with conventional limited lifetime batteries. One efficient solution to prolong the lifespan of these implementations is to integrate energy harvesting technologies into IoT systems. However, due to the characteristics of the energy harvesting technologies and the different energy requirements of the IoT systems, this integration is a challenging issue. Since Medium Access Control (MAC) layer operations are the most energy-consuming processes in wireless communications, they have undergone different modifications and enhancements in the literature to address this issue. Despite the essential role of the MAC layer to efficiently optimize the energy consumption in IoT systems, there is a gap in the literature to systematically understand the possible MAC layer improvements allowing energy harvesting integration. In this survey paper, we provide a unified framework for different wireless technologies to measure their energy consumption from a MAC operation-based perspective, returning the essential information to select the suitable energy harvesters for different communication technologies within IoT systems. Our analyses show that only 23% of the presented protocols in the literature fulfill Energy Neutral Operation (ENO) condition. Moreover, 48% of them are based on the hybrid approaches, which shows its capability to be adapted to energy harvesting. We expect this survey paper to lead researchers in academia and industry to understand the current state-of-the-art of energy harvesting MAC protocols for IoT and improve the early adoption of these protocols in IoT systems.

Improving Energy Efficiency in Internet of Things using Artificial Bee Colony Algorithm

2020 ◽  
Vol 14 ◽  
Author(s):  
M. Sivaram ◽  
V. Porkodi ◽  
Amin Salih Mohammed ◽  
S. Anbu Karuppusamy
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Artificial Bee Colony ◽  
Trust Model ◽  
Sensor Nodes ◽  
Remote Areas ◽  
Bee Colony ◽  
Important Concern ◽  
Wide Range ◽  
Iot Devices

Background: With the advent of IoT, the deployment of batteries with a limited lifetime in remote areas is a major concern. In certain conditions, the network lifetime gets restricted due to limited battery constraints. Subsequently, the collaborative approaches for key facilities help to reduce the constraint demands of the current security protocols. Aim: This work covers and combines a wide range of concepts linked by IoT based on security and energy efficiency. Specifically, this study examines the WSN energy efficiency problem in IoT and security for the management of threats in IoT through collaborative approaches and finally outlines the future. The concept of energy-efficient key protocols which clearly cover heterogeneous IoT communications among peers with different resources has been developed. Because of the low capacity of sensor nodes, energy efficiency in WSNs has been an important concern. Methods: Hence, in this paper, we present an algorithm for Artificial Bee Colony (ABC) which reviews security and energy consumption to discuss their constraints in the IoT scenarios. Results: The results of a detailed experimental assessment are analyzed in terms of communication cost, energy consumption and security, which prove the relevance of a proposed ABC approach and a key establishment. Conclusion: The validation of DTLS-ABC consists of designing an inter-node cooperation trust model for the creation of a trusted community of elements that are mutually supportive. Initial attempts to design the key methods for management are appropriate individual IoT devices. This gives the system designers, an option that considers the question of scalability.

scholarly journals Energy Efficient SWIPT Based Mobile Edge Computing Framework for WSN-Assisted IoT

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4798
Author(s):  
Fangni Chen ◽  
Anding Wang ◽  
Yu Zhang ◽  
Zhengwei Ni ◽  
Jingyu Hua
Keyword(s):  
Energy Consumption ◽  
Transmission Rate ◽  
Edge Computing ◽  
Energy Harvest ◽  
Total System ◽  
Mobile Edge Computing ◽  
Weight Factor ◽  
Iot Devices ◽  
System Variables ◽  
The Relationship

With the increasing deployment of IoT devices and applications, a large number of devices that can sense and monitor the environment in IoT network are needed. This trend also brings great challenges, such as data explosion and energy insufficiency. This paper proposes a system that integrates mobile edge computing (MEC) technology and simultaneous wireless information and power transfer (SWIPT) technology to improve the service supply capability of WSN-assisted IoT applications. A novel optimization problem is formulated to minimize the total system energy consumption under the constraints of data transmission rate and transmitting power requirements by jointly considering power allocation, CPU frequency, offloading weight factor and energy harvest weight factor. Since the problem is non-convex, we propose a novel alternate group iteration optimization (AGIO) algorithm, which decomposes the original problem into three subproblems, and alternately optimizes each subproblem using the group interior point iterative algorithm. Numerical simulations validate that the energy consumption of our proposed design is much lower than the two benchmark algorithms. The relationship between system variables and energy consumption of the system is also discussed.

scholarly journals Smart Energy Consumption of IoT With Millimeter-Wave Cognitive Radiofor 5G Cellular Network

2021 ◽  
Author(s):  
Dan Ye
Keyword(s):  
Energy Consumption ◽  
Cognitive Radio ◽  
Energy Saving ◽  
Millimeter Wave ◽  
Resource Sharing ◽  
Network Capacity ◽  
Visible Light Communications ◽  
Radio Access ◽  
Data Rates ◽  
Iot Devices

Abstract Millimeter-wave technology is rising as a crucial component for 5G radio access and other emerging ancillary wireless networks including Gb/s device-to-device communication and mobile backhaul. This paper envisions that millimeter-wave cognitive radio in 5G network is a proposed smart energy consumption solution of Internet of Things (IoT) devices. Improving resource efficiency and enhancing data rates, resource sharing is a proposed advantage over millimeter wave cognitive radio in 5G IoT network. IoT Fog collaboration is proposed to apply artificial intelligence techniques to offer important energy-saving services allowing integrated systems to perceive, reason, learn, and act intelligently in intelligent gateway control. Smart energy meters are the current energy-saving utility in the flexible deployment of IoT architecture. NarrowBand IoT (NB-IoT) delivers Low Power Wide Area access (LPWA) to a new generation of connected things in the race to 5G IoT network, reducing energy computation and achieving promising network capacity. The renewable energy strategy is a proposed energy-efficiency solution in IoT network, maximizing the power supply while minimizing power consumption. A novel kind of visible light communications (VLC) is proposed to enable mmWave cognitive radio receiver in 5G IoT network. Simulation results show the proposed solution can reap the benefits of higher data rates, more IoT device connectivity, and lower energy consumption.

scholarly journals Mobile Application for Electric Power Monitoring on Energy Consumptions at a Campus University

2018 ◽  
Vol 11 (2) ◽  
pp. 637
Author(s):  
Murizah Kassim ◽  
Maisarah Abdul Rahman ◽  
Cik Ku Haroswati Che Ku Yahya ◽  
Azlina Idris
Keyword(s):  
Energy Consumption ◽  
Electric Power ◽  
Mobile Applications ◽  
Working Hours ◽  
Mobile App ◽  
Smart Meter ◽  
University Campus ◽  
Smart Meters ◽  
Power Monitoring ◽  
Energy Consumptions

This paper presents a research on electric power monitoring prototype mobile applications development on energy consumptions in a university campus. Electric power energy consumptions always are the issue of monitoring usage especially in a broad environment. University campus faces high used of electric power, thus crucial analysis on cause of the usage is needed. This research aims to analyses electric power usage in a university campus where implemented of few smart meters is installed to monitor five main buildings in a campus university. A Monitoring system is established in collecting electric power usage from the smart meters. Data from the smart meter then is analyzed based on energy consume on 5 buildings. Results presents graph on the power energy consume and presented on mobile applications using Live Code coding. The methodology involved the setup of the smart meters, monitoring and data collected from main smart meters, analyzed electrical consumptions for 5 buildings and mobile system development to monitor. A Live Code mobile app is designed then data collected from smart meter using ION software is published in graphs. Results presents the energy consumed for 5 building during day and night. Details on maximum and minimum energy consumption presented that show load of energy used in the campus. Result present Tower 1 saved most eenergy at night which is 65% compared to block 3 which is 8% saved energy although block 3 presents the lowest energy consumption in the working hours and non-working hours. This project is significant that can help campus facility to monitor electric power used thus able to control possible results in future implementations.

scholarly journals Wireless Home Energy Meter Manager using Android: A Preliminary study

2019 ◽  
Vol 18 (3-2) ◽  
pp. 32-36
Author(s):  
Sh. Nurul Hidayah Wan Julihi ◽  
Ili Najaa Aimi Mohd Nordin ◽  
Muhammad Rusydi Muhammad Razif ◽  
Amar Faiz Zainal Abidin
Keyword(s):  
Energy Consumption ◽  
Personal Information ◽  
Current Sensor ◽  
Smart Meter ◽  
Smart Meters ◽  
Long Distance ◽  
Energy Meter ◽  
Utility Companies ◽  
Preliminary Study ◽  
To Receive

Manual home energy meter reading and billing had caused inconvenience to the utility companies due to lack of manpower to read the energy meter at each household especially in the remote area, explains the increasing number of smart meter reader in the current market. Most of the smart meters in the market do not offer safety of privacy of consumers’ personal information since the data of electricity usage is being transferred digitally to the utility companies for more accurate bills calculation. Plus, the smart meter system is also a bit pricey to be installed in the rural area. Therefore, a private system that able to read energy consumption from a DC load and calculate its bill according to the tariff is proposed. Value of current is being obtained by using ACS712 current sensor. Hall circuit in the current sensor will converts magnetic field into a proportional voltage. The proposed system allows energy meter monitoring from an Android-based smartphone by displaying the real-time energy consumption and bill on Blynk application. An interface of Blynk is developed and connected to WiFi module, ESP8266 for visualizing the energy consumption of the DC load. In conclusion, the Energy Meter transmitter part able to read, calculate and transmit value of energy consumption and current bills to the Blynk application and Blynk application able to receive and show all the data transmitted at the present time. This system will be further improved for long-distance monitoring of electrical appliances used at home.

scholarly journals Two Is Not Enough: Privacy Assessment of Aggregation Schemes in Smart Metering

2017 ◽  
Vol 2017 (4) ◽  
pp. 198-214 ◽  
Author(s):  
Niklas Buescher ◽  
Spyros Boukoros ◽  
Stefan Bauregger ◽  
Stefan Katzenbeisser
Keyword(s):  
Energy Consumption ◽  
Personal Data ◽  
Smart Meters ◽  
Trade Off ◽  
World Energy ◽  
Protection Mechanisms ◽  
Significant Probability ◽  
Aggregation Scheme ◽  
Energy Provider ◽  
World Energy Consumption

Abstract The widespread deployment of smart meters that frequently report energy consumption information, is a known threat to consumers’ privacy. Many promising privacy protection mechanisms based on secure aggregation schemes have been proposed. Even though these schemes are cryptographically secure, the energy provider has access to the plaintext aggregated power consumption. A privacy trade-off exists between the size of the aggregation scheme and the personal data that might be leaked, where smaller aggregation sizes leak more personal data. Recently, a UK industrial body has studied this privacy trade-off and identified that two smart meters forming an aggregate, are sufficient to achieve privacy. In this work, we challenge this study and investigate which aggregation sizes are sufficient to achieve privacy in the smart grid. Therefore, we propose a flexible, yet formal privacy metric using a cryptographic game based definition. Studying publicly-available, real world energy consumption datasets with various temporal resolutions, ranging from minutes to hourly intervals, we show that a typical household can be identified with very high probability. For example, we observe a 50% advantage over random guessing in identifying households for an aggregation size of 20 households with a 15-minutes reporting interval. Furthermore, our results indicate that single appliances can be identified with significant probability in aggregation sizes up to 10 households.

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