Smart IoT Meters for Smart Living

2019 ◽  
pp. 253-264
Author(s):  
Ramesh Kesavan ◽  
Pushpa Jaculine J.
Keyword(s):  
Traffic Control ◽  
Water Distribution ◽  
Solid Waste Management ◽  
Smart Cities ◽  
Smart Devices ◽  
Infrastructure Management ◽  
Smart Meters ◽  
Information And Communication ◽  
Automatic Parking ◽  
Gas Consumption

Smart cities and smart villages provide technology-based, sophisticated, and better lifestyles to their citizens. Smart cities include traffic control, transport management, managing spare resources like power and water, solid waste management, e-health monitoring, infrastructure management based on internet of things (IoT) technology. IoT is a technique that combines sensors, electronic devices, information and communication technology, and software for the social wellbeing of the common man. In recent years, many IoT-based smart devices, namely smart garbage bins, automatic parking system, smart electric meters, supervisory control and data acquisition (SCADA) for water distribution, have been devised and used successfully in many cities. Mostly, smart meters are used in recording electric power and gas consumption.

scholarly journals Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events

2021 ◽  
Vol 19 (3) ◽  
Author(s):  
Luca Foschini ◽  
Giuseppe Martuscelli ◽  
Rebecca Montanari ◽  
Michele Solimando
Keyword(s):  
Information And Communication Technologies ◽  
Smart Cities ◽  
Communication Technologies ◽  
Smart Devices ◽  
Mobile Crowdsensing ◽  
Share Data ◽  
Information And Communication ◽  
Emergency Scenarios ◽  
The City

AbstractSmart cities use Information and Communication Technologies (ICT) to enrich existing public services and to improve citizens’ quality of life. In this scenario, Mobile CrowdSensing (MCS) has become, in the last few years, one of the most prominent paradigms for urban sensing. MCS allow people roaming around with their smart devices to collectively sense, gather, and share data, thus leveraging the possibility to capture the pulse of the city. That can be very helpful in emergency scenarios, such as the COVID-19 pandemic, that require to track the movement of a high number of people to avoid risky situations, such as the formation of crowds. In fact, using mobility traces gathered via MCS, it is possible to detect crowded places and suggest people safer routes/places. In this work, we propose an edge-anabled mobile crowdsensing platform, called ParticipAct, that exploits edge nodes to compute possible dangerous crowd situations and a federated blockchain network to store reward states. Edge nodes are aware of all critical situation in their range and can warn the smartphone client with a smart push notification service that avoids firing too many messages by adapting the warning frequency according to the transport and the specific subarea in which clients are located.

scholarly journals Block chain Technology for Smart City and its Security Threats

2019 ◽  
Vol 8 (4S2) ◽  
pp. 755-759
Keyword(s):  
Smart City ◽  
Smart Cities ◽  
Smart Devices ◽  
The Public ◽  
Blockchain Technology ◽  
Use Of Resources ◽  
The People ◽  
Information And Communication ◽  
Block Chain ◽  
Areas Of Interest

The current modern year shows quick growth in metropolitanization and population growth of the world that causes various impacts on environmental, social and economic problems. The problems aroused in society influence the livelihood of the people and excellence of existence. “Smart City” passes many opportunities to resolve these urban inconveniences and unsolved issues. The chief fact of a smart city is to create the finest use of resources gathered from the public, make available with reliable services to the citizens with enriched quality and efficiently enhance the day to day life standard of peoples. In the smart city establishment Information and Communication Technology (ICT) shows greater impact. Block chain is a intensifying technology with many excellent aspects likely intelligibility, automation and security. A characteristic of block chain is supportive in improving the standard services and advances the expansion which applies information technology that integrates several areas of interest. Block chain manages the business, physical and social infrastructures to provide effective services to needed users. With the advancement of technologies namely interconnected networks, cloud computing and the Internet of Things (IoT), for smart cities can carry creative as well as novel solutions. Smart cities can offer people with interface and association between the general public as well as the local government. Despite several possible remunerations, digital interruption postures many objections related to privacy and along with information security. Here in this paper, we discussed in detail about blockchain technology and the security framework that assimilates the smart devices and blockchain technology together.

scholarly journals Modeling and clustering water demand patterns from real-world smart meter data

2017 ◽  
Vol 10 (2) ◽  
pp. 75-82 ◽  
Author(s):  
Nicolas Cheifetz ◽  
Zineb Noumir ◽  
Allou Samé ◽  
Anne-Claire Sandraz ◽  
Cédric Féliers ◽  
...  
Keyword(s):  
Time Series ◽  
Water Consumption ◽  
Water Demand ◽  
Smart Grids ◽  
Water Distribution ◽  
Smart Cities ◽  
Distribution Network ◽  
Seasonal Patterns ◽  
Smart Meters ◽  
Time Step

Abstract. Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, manage billing and propose new customer services. With the emergence of smart grids, based on automated meter reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and also produces K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest water distribution network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow one to highlight the effectiveness of the proposed methodology.

scholarly journals Modeling and Clustering Water Demand Patterns from Real-World Smart Meter Data

2017 ◽  
Author(s):  
Nicolas Cheifetz ◽  
Zineb Noumir ◽  
Allou Samé ◽  
Anne-Claire Sandraz ◽  
Cédric Féliers ◽  
...  
Keyword(s):  
Time Series ◽  
Water Consumption ◽  
Water Demand ◽  
Smart Grids ◽  
Water Distribution ◽  
Smart Cities ◽  
Distribution Network ◽  
Seasonal Patterns ◽  
Smart Meters ◽  
Time Step

<p><strong>Abstract.</strong> Nowadays, drinking water utilities need an acute comprehension of the water demand on their distribution network, in order to efficiently operate the optimization of resources, the management of billing and to propose new customer services. With the emergence of smart grids, based on Automated Meter Reading (AMR), a better understanding of the consumption modes is now accessible for smart cities with more granularities. In this context, this paper evaluates a novel methodology for identifying relevant usage profiles from the water consumption data produced by smart meters. The methodology is fully data-driven using the consumption time series which are seen as functions or curves observed with an hourly time step. First, a Fourier-based additive time series decomposition model is introduced to extract seasonal patterns from time series. These patterns are intended to represent the customer habits in terms of water consumption. Two functional clustering approaches are then used to classify the extracted seasonal patterns: the functional version of K-means, and the Fourier REgression Mixture (FReMix) model. The K-means approach produces a hard segmentation and K representative prototypes. On the other hand, the FReMix is a generative model and produces also K profiles as well as a soft segmentation based on the posterior probabilities. The proposed approach is applied to a smart grid deployed on the largest Water Distribution Network (WDN) in France. The two clustering strategies are evaluated and compared. Finally, a realistic interpretation of the consumption habits is given for each cluster. The extensive experiments and the qualitative interpretation of the resulting clusters allow to highlight the effectiveness of the proposed methodology.</p>

Technologies Disability and Inclusion

2018 ◽  
Author(s):  
Tomas Brusell
Keyword(s):  
Social Media ◽  
Augmented Reality ◽  
Information And Communication Technologies ◽  
Future Development ◽  
Smart Cities ◽  
Communication Technologies ◽  
Modern Technology ◽  
The Social ◽  
The Disabled ◽  
Information And Communication

When modern technology permeates every corner of life, there are ignited more and more hopes among the disabled to be compensated for the loss of mobility and participation in normal life, and with Information and Communication Technologies (ICT), Exoskeleton Technologies and truly hands free technologies (HMI), it's possible for the disabled to be included in the social and pedagogic spheres, especially via computers and smartphones with social media apps and digital instruments for Augmented Reality (AR) .In this paper a nouvel HMI technology is presented with relevance for the inclusion of disabled in every day life with specific focus on the future development of "smart cities" and "smart homes".

PRODUCTION AND USE OF SOLID RECOVERED FUEL FOR A RESILIENT SOLID WASTE MANAGEMENT IN SMART CITIES-EU APPROACH

2019 ◽  
Vol 7 (3) ◽  
pp. 1
Author(s):  
FULLER AARON ◽  
MILLER EVA ◽  
MAIER JÖRG ◽  
GLORIUS THOMAS ◽  
SCHEFFKNECHT GÜNTER ◽  
...  
Keyword(s):  
Waste Management ◽  
Solid Waste ◽  
Solid Waste Management ◽  
Smart Cities

scholarly journals Privacy-Preserving Smart Road-Pricing System with Trustworthiness Evaluation in VANETs

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3658
Author(s):  
Qingfeng Zhu ◽  
Sai Ji ◽  
Jian Shen ◽  
Yongjun Ren
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Location Privacy ◽  
Vehicular Ad Hoc Networks ◽  
Intelligent Transportation System ◽  
Smart Cities ◽  
Security Analysis ◽  
Geographical Location ◽  
Experimental Simulation ◽  
Control Center

With the advanced development of the intelligent transportation system, vehicular ad hoc networks have been observed as an excellent technology for the development of intelligent traffic management in smart cities. Recently, researchers and industries have paid great attention to the smart road-tolling system. However, it is still a challenging task to ensure geographical location privacy of vehicles and prevent improper behavior of drivers at the same time. In this paper, a reliable road-tolling system with trustworthiness evaluation is proposed, which guarantees that vehicle location privacy is secure and prevents malicious vehicles from tolling violations at the same time. Vehicle route privacy information is encrypted and uploaded to nearby roadside units, which then forward it to the traffic control center for tolling. The traffic control center can compare data collected by roadside units and video surveillance cameras to analyze whether malicious vehicles have behaved incorrectly. Moreover, a trustworthiness evaluation is applied to comprehensively evaluate the multiple attributes of the vehicle to prevent improper behavior. Finally, security analysis and experimental simulation results show that the proposed scheme has better robustness compared with existing approaches.

scholarly journals An Efficient Management Platform for Developing Smart Cities: Solution for Real-Time and Future Crowd Detection

Electronics ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 765
Author(s):  
David Garcia-Retuerta ◽  
Pablo Chamoso ◽  
Guillermo Hernández ◽  
Agustín San Román Guzmán ◽  
Tan Yigitcanlar ◽  
...  
Keyword(s):  
Smart Cities ◽  
Open Data ◽  
Climate Data ◽  
Smart Meters ◽  
Security Systems ◽  
Crowd Management ◽  
Management Platform ◽  
Efficient Management ◽  
Pedestrian Traffic ◽  
The City

A smart city is an environment that uses innovative technologies to make networks and services more flexible, effective, and sustainable with the use of information, digital, and telecommunication technologies, improving the city’s operations for the benefit of its citizens. Most cities incorporate data acquisition elements from their own systems or those managed by subcontracted companies that can be used to optimise their resources: energy consumption, smart meters, lighting, irrigation water consumption, traffic data, camera images, waste collection, security systems, pollution meters, climate data, etc. The city-as-a-platform concept is becoming popular and it is increasingly evident that cities must have efficient management systems capable of deploying, for instance, IoT platforms, open data, etc., and of using artificial intelligence intensively. For many cities, data collection is not a problem, but managing and analysing data with the aim of optimising resources and improving the lives of citizens is. This article presents deepint.net, a platform for capturing, integrating, analysing, and creating dashboards, alert systems, optimisation models, etc. This article shows how deepint.net has been used to estimate pedestrian traffic on the streets of Melbourne (Australia) using the XGBoost algorithm. Given the current situation, it is advisable not to transit urban roads when overcrowded, thus, the model proposed in this paper (and implemented with deepint.net) facilitates the identification of areas with less pedestrian traffic. This use case is an example of an efficient crowd management system, implemented and operated via a platform that offers many possibilities for the management of the data collected in smart territories and cities.

Smart Traffic Control: Identifying Driving-Violations using Fog Devices with Vehicular Cameras in Smart Cities

2021 ◽  
pp. 102986
Author(s):  
M. Mazhar Rathore ◽  
Anand Paul ◽  
Seungmin Rho ◽  
Murad Khan ◽  
S. Vimal ◽  
...  
Keyword(s):  
Traffic Control ◽  
Smart Cities ◽  
Smart Traffic
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