Eranga Bandara, Xueping Liang, Peter B. Foytik, S. Shetty, N. Ranasinghe, K. Zoysa
{"title":"Bassa-Scalable Blockchain Architecture for Smart Cities","authors":"Eranga Bandara, Xueping Liang, Peter B. Foytik, S. Shetty, N. Ranasinghe, K. Zoysa","doi":"10.1109/ISC251055.2020.9239072","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239072","url":null,"abstract":"Smart cities will depend on reliable Internet of things to effectively provide residential and commercial services. Smart city applications generate vast amount of data and will need the infrastructure to support high transaction throughput. The data associated with smart cities can include sensitive information and there is a need to guarantee the security and privacy through a blockchain-based decentralized infrastructure. Current blockchain environments face several challenges, such as, lack of high transaction throughput, high scalability, real-time transaction processing, and back-end stress operations, etc. In this paper, we propose “Bassa”, a blockchain platform that will meet the aforementioned challenges. Bassa employs a Apache Kafka based consensus and ‘validate-execute-group” blockchain architecture to realize real-time transaction. Bassa’s smart contract platform realizes concurrent transaction by leveraging actor-based concurrency.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115282270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Characterizing Road Conditions Via Smart Mobile Crowd Sourcing","authors":"Dustin Shorter, Sami Alshammari, Sejun Song","doi":"10.1109/ISC251055.2020.9239020","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239020","url":null,"abstract":"Bad road conditions can cause vehicle damage and create hazardous driving conditions. Current reporting methods for bad road conditions is a burden for the reporter, so much so that these conditions might not be reported. With current smartphone technology this reporting method can be greatly improved. Smartphones come with an accelerometer and GPS positioning on-board. Utilizing these sensors, once the application is installed and run, a smartphone user can gather bad road conditions automatically while driving. Then the user can upload the data to the server. These road conditions are then classified and optionally displayed on a map while the user is driving. The potential for finding bad road conditions is greatly increases with crowd sourcing. When the road condition data is analyzed an algorithm is used to determine the size of the bad road condition and how many samples are needed. Even though the smartphone might not have the sampling rate of a dedicated accelerometer, its potential for gather large amounts of data using crowd sourcing and ease of use outweighs this deficiency.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125876033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ramon A. Briseño, J. López, Ma. Roció Maciel Arellano, Víctor M. Larios-Rosillo, J. R. Beltrán-Ramírez, Carlos López-Zaragoza
{"title":"Digital Platform to promote sustainable mobility and COVID-19 infections reduction: a use case in the Guadalajara metropolitan area","authors":"Ramon A. Briseño, J. López, Ma. Roció Maciel Arellano, Víctor M. Larios-Rosillo, J. R. Beltrán-Ramírez, Carlos López-Zaragoza","doi":"10.1109/ISC251055.2020.9239013","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239013","url":null,"abstract":"This work proposes a digital platform based in a multi-agent system to plot the different mobility alternatives to counteract the agglomerations in public transport and therefore decrease COVID-19 infections in the GDL. Following the recommendations of the World Health Organization (WHO) in the face of the health emergency of COVID-19, mainly keeping a healthy distance, the GDL can integrate sustainable mobility as the public bicycle system and reduce the users in regular transport routes to safe levels. For that endeavor, we develop an analysis of the behavior of the trips in the public transport of Guadalajara to explore the possibility of substituting the short transfers of bus travel by bicycle travels using the existing public bicycle infrastructure. We introduce a multi-agent simulation to plot different scenarios of mobility moving bicycles and buses. In this preliminary work, we show possibilities of the simulation integrating as variables not only the risk of COVID-19 infection but also the impact on economy and traffic reduction, CO2 Footprint, and health achieved with this multimodal mobility simulation. Also, the simulation can help to incentivize safer and efficient mobility strategies in the public transport system to reduce the use of private vehicles.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"474 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115458655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Xie, Dongxiao Wang, Chun Sing Lai, R. Wu, Jiachang Huang, L. Lai
{"title":"Optimal Sizing of Battery Energy Storage System in Smart Microgrid with Air-conditioning Resources","authors":"C. Xie, Dongxiao Wang, Chun Sing Lai, R. Wu, Jiachang Huang, L. Lai","doi":"10.1109/ISC251055.2020.9239044","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239044","url":null,"abstract":"In the microgrid with high photovoltaic (PV) penetration, the optimal sizing of battery energy storage system (BESS) has been a trending research topic in recent years. Simultaneously, the high energy consumption of air-conditioned households is attracting increasing attention currently. In this paper, an optimal sizing method of BESS is developed for a smart microgrid with PV systems and air-conditioning resources. The proposed model is divided into two layers. In the first layer, the initial size of BESS is determined with consideration of photovoltaic output power and thermal buffering characteristics of air-conditioned households. In the second layer, the optimal size of BESS is proposed to minimize the system overall cost including BESS construction investment and microgrid system operation cost. The model is solved by differential evolutionary algorithm and iterative algorithms. Case studies demonstrate the effectiveness of the proposed method.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122529974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic Assignment of Emergency Vehicles in Response to Sensors-based Generated Alarms in Smart City Scenarios","authors":"D. G. Costa, F. Vasques, A. Aguiar, P. Portugal","doi":"10.1109/ISC251055.2020.9239062","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239062","url":null,"abstract":"The adoption of sensors-based monitoring systems supported by Internet of Things technologies has opened new possibilities for data retrieving and processing in urban areas. Among such possibilities, emergencies management is expected to play an important role in how modern cities will evolve, reducing the negative impacts of critical events and improving the quality of life perceived by their inhabitants. Actually, when an emergency is detected and alerted, emergency vehicles, notably ambulances, fire trucks, police cars and transit agents vehicles, should be quickly assigned to respond to that situation, as soon as possible. In this context, we propose a dynamic algorithm to automatically assign emergency vehicles in smart city scenarios, exploiting for that a sensors-based emergency detection system to provide emergency alerts. The proposed algorithm can then be used to quickly assign a number of emergency vehicles in the first moments of an emergency, which can potentially save lives and improve existing crisis management applications in smart cities.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122855111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Neural Network-based Model Predictive Control Approach for Buildings Comfort Management","authors":"R. Eini, S. Abdelwahed","doi":"10.1109/ISC251055.2020.9239051","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239051","url":null,"abstract":"This paper proposes a model predictive control (MPC) approach incorporated with machine learning to control the energy consumption and occupants’ comfort (thermal and visual comfort) in a smart building. Neural networks (NN)s are developed to learn and predict the building’s comfort specifications, environmental conditions, and power consumption. Based on the predicted data, MPC provides optimal control inputs for the thermal and lighting systems to achieve the desired performance. In contrast to the existing building control frameworks, our proposed learning-based control method incorporates the occupant-related parameters in the control loop, which enhances the prediction accuracy and control performance. Our proposed learning-based MPC approach is implemented on a building, simulated in EnergyPlus software, and its performance is compared with that of a model-based building control framework. From the simulation results, our control method performs significantly better than the conventional MPC in maintaining residents’ comfort and reducing energy consumption.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128432585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ely Bernardi, M. Y. Miyake, A. Santos, Marlene P. Merichelli, Matheus J. Pereira, Matheus Polkorny
{"title":"Brazilian scenarios for smart cities deployment from public policies perspectives","authors":"Ely Bernardi, M. Y. Miyake, A. Santos, Marlene P. Merichelli, Matheus J. Pereira, Matheus Polkorny","doi":"10.1109/ISC251055.2020.9239096","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239096","url":null,"abstract":"Although Information and Communication Technology - ICT solutions have been used for a long time in various sectors of the economy, recent developments in Communications, IoT, Data Science and Artificial Intelligence have brought very attractive possibilities for their wider adoption, especially with regard to cities and its citizens.In this article, some aspects of the international and the Brazilian technical regulations are addressed, with special attention to issues of interest to cities. The General Data Protection Law of Brazil is highlighted.Some specific projects and initiatives related to smart cities are also presented and commented on, such as the National IoT Plan and its consequences, besides other initiatives to address smart cities.Additionally, some aspects of present days combat actions in the Covid-19 pandemic and its relationships with public policies applied to cities are highlighted.Finally, considerations about the need for effective and efficient public policies to reinforce the resilience of cities, including tackling biological hazards, are addressed.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124175378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karthik Gurunathan, Yadamakanti Sushmitha Reddy, R. Dash, J. L. Risco-Martín, Sara Pérez-Carabaza, E. Besada-Portas
{"title":"Minimum Time Search in Unmanned Aerial Vehicles using Ant Colony Optimisation based Realistic Scenarios","authors":"Karthik Gurunathan, Yadamakanti Sushmitha Reddy, R. Dash, J. L. Risco-Martín, Sara Pérez-Carabaza, E. Besada-Portas","doi":"10.1109/ISC251055.2020.9239065","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239065","url":null,"abstract":"Unmanned aerial vehicles (UAV), or drones, are aircrafts without a human pilot on board. UAVs find a target in minimum time using Minimum Time Search (MTS) methods. Different optimisation paradigms, such as cross-entropy optimisation (CEO) and ant-colony optimisation (ACO) can be used for MTS. In this work, a set of simulation scenarios has been designed to test the ACO solution to the MTS problem. Simulations performed for each scenario take into account a heuristic function and its effect on the probability of detection of target and estimated time for detection. The results obtained for various scenarios based on external and internal factors in UAV trajectory planning (size of search grid, target distribution, etc.) are compared to categorise the best set of such factors across four input domains. Results show a huge variance in the role played by the heuristic function and choice of feature thresholds for each scenario.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123524732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Filling Missing Values in Spatial-temporal Data Collected from Traffic Sensors","authors":"Fábio Oliveira, Ana Paula Rocha","doi":"10.1109/ISC251055.2020.9239016","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239016","url":null,"abstract":"Intelligent transportation systems (ITS) are critical to any smart city strategy. They are used to optimize the flow of urban traffic which in turn leads to a reduction in time spent traveling. In order for ITS to work properly, sensors that collect real-time traffic flow information from streets and highways are required so the ITS can know the current state of the traffic. However, such sensors are prone to failures and network faults. This poses a serious hindrance when performing data analysis and knowledge extraction on sensor data due to the fact that such data is composed of noisy and missing values. In this work, we benchmark several deep learning based methods for filling missing values in a dataset collected from 2013 to 2015 in the city of Oporto, Portugal. The dataset is composed of readings of 26 sensors that measure traffic information in 5 minute intervals. Around 12% of all values are missing.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124052993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Barulli, Alessandro Ciociola, M. Cocca, L. Vassio, Danilo Giordano, M. Mellia
{"title":"On Scalability of Electric Car Sharing in Smart Cities","authors":"M. Barulli, Alessandro Ciociola, M. Cocca, L. Vassio, Danilo Giordano, M. Mellia","doi":"10.1109/ISC251055.2020.9239086","DOIUrl":"https://doi.org/10.1109/ISC251055.2020.9239086","url":null,"abstract":"In this paper we analyze which are the design options that would impact a free floating electric car sharing system performance and costs, studying how the system would scale with an increase in the intensity of the demand. We consider the case study of the city of Turin, for which we leverage hundred of thousands of actual rentals from a (combustion-based) car sharing system to derive an accurate demand model. Armed with this, we consider the transition to electric cars and the need to deploy a charging station infrastructure.Using a realistic simulator, we present the impact of system design options, like the number of charging poles, their allotment, and the number of cars. We first consider performance indicators, like fraction of satisfied demand and working hours system has to spend to bring to charge vehicles. Then we map these figures into revenues and costs, projecting economical indicators. At last, we investigate the scalability of the whole system, i.e., how performance and costs scale when the demand increases. Our results show that concentrating the charging stations in key places is instrumental to optimize car distribution in the city to better intercept the demand. Considering system scalability, the charging infrastructure must intuitively grow proportionally with the mobility demand. Interestingly instead, the fleet size can grow much slower, showing some nice economy of scale gains.","PeriodicalId":201808,"journal":{"name":"2020 IEEE International Smart Cities Conference (ISC2)","volume":"106 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127570193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}