Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922095
Alessandro Seravalli, Mariaelena Busani, Simone Venturi, A. Brutti, C. Petrovich, Angelo Frascella, F. Paolucci, M. Di Felice, M. Lombardi, Elena Bellodi, Riccardo Zese, Francesco Bertasi, Elia Balugani, Alket Cecaj, R. Gamberini, M. Mamei, Marco Picone
Novel and widespread ICT and Internet of Things (IoT) technology can provide fine-grained real-time information to the tourist sector, both to support the demand side (tourists) and the supply side (managers and organizers). We present the POLIS-EYE project that aims to build decision-support systems helping tourist-managers to organize and optimize policies and resources. In particular, we focus on a service to monitor and forecast people presence in tourist areas by combining heterogeneous datasets with a special focus on data collected from the mobile phone network.
{"title":"Towards Smart Cities for Tourism: the POLIS-EYE Project","authors":"Alessandro Seravalli, Mariaelena Busani, Simone Venturi, A. Brutti, C. Petrovich, Angelo Frascella, F. Paolucci, M. Di Felice, M. Lombardi, Elena Bellodi, Riccardo Zese, Francesco Bertasi, Elia Balugani, Alket Cecaj, R. Gamberini, M. Mamei, Marco Picone","doi":"10.1109/ISC255366.2022.9922095","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922095","url":null,"abstract":"Novel and widespread ICT and Internet of Things (IoT) technology can provide fine-grained real-time information to the tourist sector, both to support the demand side (tourists) and the supply side (managers and organizers). We present the POLIS-EYE project that aims to build decision-support systems helping tourist-managers to organize and optimize policies and resources. In particular, we focus on a service to monitor and forecast people presence in tourist areas by combining heterogeneous datasets with a special focus on data collected from the mobile phone network.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116934790","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922015
D. Cenni, Chenyang Wang, Ahmed Ferdous Antor, Qi Han
Traffic prediction can help people make better travel plans by avoiding traffic jams, and also help the city to more proactively deploy emergency response vehicles. The continuous growth of social networks made possible the use of large amounts of data for traffic prediction. One of the biggest challenges in this regard is to acquire and process crowdsourced data to build effective models for traffic prediction. In this paper we propose a novel framework for processing crowdsourced data, with the goal of building effective traffic prediction models. We apply our solution to predict traffic related events in the busiest interstate in Colorado (USA), using Waze crowdsourced data. The events considered in the dataset are moderate jam, heavy jam, and stand still jam. In addition to traffic alerts crowdsourced data via Waze, we also use the traffic speed and weather data. The proposed solution proves to be effective and highly scalable, and the model's best accuracy on the test set is ~76%. This approach can be easily generalized in order to develop models that are able to provide effective traffic related predictions.
{"title":"An Integrated Platform for Mining Crowdsourced Data for Smart Traffic Prediction","authors":"D. Cenni, Chenyang Wang, Ahmed Ferdous Antor, Qi Han","doi":"10.1109/ISC255366.2022.9922015","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922015","url":null,"abstract":"Traffic prediction can help people make better travel plans by avoiding traffic jams, and also help the city to more proactively deploy emergency response vehicles. The continuous growth of social networks made possible the use of large amounts of data for traffic prediction. One of the biggest challenges in this regard is to acquire and process crowdsourced data to build effective models for traffic prediction. In this paper we propose a novel framework for processing crowdsourced data, with the goal of building effective traffic prediction models. We apply our solution to predict traffic related events in the busiest interstate in Colorado (USA), using Waze crowdsourced data. The events considered in the dataset are moderate jam, heavy jam, and stand still jam. In addition to traffic alerts crowdsourced data via Waze, we also use the traffic speed and weather data. The proposed solution proves to be effective and highly scalable, and the model's best accuracy on the test set is ~76%. This approach can be easily generalized in order to develop models that are able to provide effective traffic related predictions.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116986268","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9921757
Daniela Renga, Gianmarco Centonze, M. Meo
Due to sustainability concerns raised by the transportation sector, still relying mostly on oil as main energy source, urban mobility is quickly shifting towards the adoption of electric vehicles (EVs), The EV charging process should heavily rely on Renewable Energy Sources (RES) and be smartly scheduled to promote sustainability and pollution reduction. In this context, renewable powered Battery Swapping Stations (BSS) represent a promising solution to enable sustainable and feasible e-mobility. Focusing on a BSS powered by photovoltaic panels, we investigate the issue of properly dimensioning its capacity (in terms of number of sockets) and the renewable energy supply to satisfy the battery swapping demand, trading off cost, Quality of Service and feasibility constraints. In addition, we analyse the potential benefits of smart scheduling strategies for battery recharging. Our results show that considerable cost saving of up to almost 40% can be achieved with a local RE supply to power the BSS. Furthermore, a proper tuning of the scheduling strategy configuration parameters is required to better trade off cost and Quality of Service, based on the desired performance targets.
{"title":"Renewable powered Battery Swapping Stations for sustainable urban mobility","authors":"Daniela Renga, Gianmarco Centonze, M. Meo","doi":"10.1109/ISC255366.2022.9921757","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9921757","url":null,"abstract":"Due to sustainability concerns raised by the transportation sector, still relying mostly on oil as main energy source, urban mobility is quickly shifting towards the adoption of electric vehicles (EVs), The EV charging process should heavily rely on Renewable Energy Sources (RES) and be smartly scheduled to promote sustainability and pollution reduction. In this context, renewable powered Battery Swapping Stations (BSS) represent a promising solution to enable sustainable and feasible e-mobility. Focusing on a BSS powered by photovoltaic panels, we investigate the issue of properly dimensioning its capacity (in terms of number of sockets) and the renewable energy supply to satisfy the battery swapping demand, trading off cost, Quality of Service and feasibility constraints. In addition, we analyse the potential benefits of smart scheduling strategies for battery recharging. Our results show that considerable cost saving of up to almost 40% can be achieved with a local RE supply to power the BSS. Furthermore, a proper tuning of the scheduling strategy configuration parameters is required to better trade off cost and Quality of Service, based on the desired performance targets.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"20 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120927713","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922308
D. Esztergár-Kiss, Alireza Ansariyar, Geza Katona
To provide seamless information for the travelers, an effective transnational door-to-door journey planner is required, where information from different operators, combined solutions, and value-added parameters appear in a realistic environment. Thus, the aim is to support seamless mobility solutions and create multimodal transport networks connecting separate systems. The elaborated method realizes this by identifying the potential exchange points between separate networks and by filtering the suitable exchange points to run the routing algorithm between the local journey planners. The proposed solution builds on a flexible algorithm, which parameters can be easily updated and extended. In case of any changes, using the formulated theoretical background, an up-to-date and realistic implementation can be derived from the foundations of the framework. In addition, the elaborated method is fully capable to cover wide geographical areas and to provide a transferable solution.
{"title":"Interconnecting Separate Transportation Systems by Introducing Exchange Points","authors":"D. Esztergár-Kiss, Alireza Ansariyar, Geza Katona","doi":"10.1109/ISC255366.2022.9922308","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922308","url":null,"abstract":"To provide seamless information for the travelers, an effective transnational door-to-door journey planner is required, where information from different operators, combined solutions, and value-added parameters appear in a realistic environment. Thus, the aim is to support seamless mobility solutions and create multimodal transport networks connecting separate systems. The elaborated method realizes this by identifying the potential exchange points between separate networks and by filtering the suitable exchange points to run the routing algorithm between the local journey planners. The proposed solution builds on a flexible algorithm, which parameters can be easily updated and extended. In case of any changes, using the formulated theoretical background, an up-to-date and realistic implementation can be derived from the foundations of the framework. In addition, the elaborated method is fully capable to cover wide geographical areas and to provide a transferable solution.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125805030","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922454
Francesco Martella, M. Fazio, Giuseppe Ciulla, Roberto Di Bernardo, A. Celesti, Valeria Lukaj, Mario Colosi, M. D. Gangi, M. Villari
Urban areas are evolving towards systems based on sustainable mobility. In particular, thanks to technologies such as Big Data analysis, Cloud, Edge Computing, and IoT, it is possible to design both decision support services for the management of smart cities and services for users. The proposed work presents an innovative device for the safety of cyclists in urban areas. The device is designed to ensure continuous connectivity. Connectivity can be global (via internet) or local thanks to the use of the mesh network. Furthermore, the designed infrastructure provides cyclists with real-time information on the urban area they are crossing, starting from the data collected by the smart city. During the implementation phase, it was of particular interest to test the functioning of the mesh and the energy performance of the device in the field.
{"title":"An Edge System for the Safety of Cyclists in the Urban Area","authors":"Francesco Martella, M. Fazio, Giuseppe Ciulla, Roberto Di Bernardo, A. Celesti, Valeria Lukaj, Mario Colosi, M. D. Gangi, M. Villari","doi":"10.1109/ISC255366.2022.9922454","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922454","url":null,"abstract":"Urban areas are evolving towards systems based on sustainable mobility. In particular, thanks to technologies such as Big Data analysis, Cloud, Edge Computing, and IoT, it is possible to design both decision support services for the management of smart cities and services for users. The proposed work presents an innovative device for the safety of cyclists in urban areas. The device is designed to ensure continuous connectivity. Connectivity can be global (via internet) or local thanks to the use of the mesh network. Furthermore, the designed infrastructure provides cyclists with real-time information on the urban area they are crossing, starting from the data collected by the smart city. During the implementation phase, it was of particular interest to test the functioning of the mesh and the energy performance of the device in the field.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"257 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122933650","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922309
P. Katrakazas, Theodora Kallinolitou, Stella Markopoulou, Argyro Chronopoulou
Internet-of-Things (IoT) has the potential to create new services and markets by allowing the exploration of new, often completely different ways of doing things, based on the clustering and aggregation of data from different sources and fields of activity. As technology advances, new ethical, legal, and technological concerns arise. In this paper, we present five key pillars of innovation towards privacy-preserving edge computing, regarding smart sampling of IoT devices, anonymous authentication and consent management, dynamic data-driven pattern management, opportunistic IoT clustering, distributed IoT data governance, and resource integrity validation. The overall concept of this paper, is to create a comprehensive methodological framework and toolset for definition, deployment and operation of privacy-compliant IoT platforms tailored to specific use-cases. During this process we are not creating “yet another IoT platform”., but rather building upon past efforts to the maximum extent possible. This approach takes into consideration existing solutions in the following areas: high-level concepts and standards; integration and interoperability frameworks; IoT platforms and infrastructural elements.
{"title":"A Toolchain and Interoperability Framework to enhance privacy and individual control at the Edge","authors":"P. Katrakazas, Theodora Kallinolitou, Stella Markopoulou, Argyro Chronopoulou","doi":"10.1109/ISC255366.2022.9922309","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922309","url":null,"abstract":"Internet-of-Things (IoT) has the potential to create new services and markets by allowing the exploration of new, often completely different ways of doing things, based on the clustering and aggregation of data from different sources and fields of activity. As technology advances, new ethical, legal, and technological concerns arise. In this paper, we present five key pillars of innovation towards privacy-preserving edge computing, regarding smart sampling of IoT devices, anonymous authentication and consent management, dynamic data-driven pattern management, opportunistic IoT clustering, distributed IoT data governance, and resource integrity validation. The overall concept of this paper, is to create a comprehensive methodological framework and toolset for definition, deployment and operation of privacy-compliant IoT platforms tailored to specific use-cases. During this process we are not creating “yet another IoT platform”., but rather building upon past efforts to the maximum extent possible. This approach takes into consideration existing solutions in the following areas: high-level concepts and standards; integration and interoperability frameworks; IoT platforms and infrastructural elements.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128369237","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922487
Y. Kishino, Yoshinari Shirai, Koh Takeuchi, Shin Mizutani, Takayuki Suyama, F. Naya, N. Ueda
Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis of garbage amounts using national census data. By simply mounting motion sensors on garbage trucks and using activity recognition and multiple regression analysis, we were able to obtain significant and illuminating information.
{"title":"District Characteristics Analysis with Regional Garbage Amount Estimation Using Vehicle- Mounted Motion Sensors","authors":"Y. Kishino, Yoshinari Shirai, Koh Takeuchi, Shin Mizutani, Takayuki Suyama, F. Naya, N. Ueda","doi":"10.1109/ISC255366.2022.9922487","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922487","url":null,"abstract":"Garbage is inextricably linked with our daily lives, and solid waste collection is one of the essential local government services. We investigate a method that estimates regional amounts of garbage using motion sensors mounted on garbage trucks. In this paper, we report the results of our analysis of garbage amounts using national census data. By simply mounting motion sensors on garbage trucks and using activity recognition and multiple regression analysis, we were able to obtain significant and illuminating information.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124683571","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9921961
Xiangyu Kong, Guangyu Zou, Heng Qi, Jiafu Tang
This paper studies an Online-to-Offline food delivery problem (OFDP) which can be viewed as a combination of variants of vehicle routing problems (VRPs). First, We define and model the OFDP mathematically. Then, we propose a novel adaptive parameters genetic algorithm with local search (APGALS) to solve the OFDP. The adaptive parameters method dynamically adjusts the crossover and mutation rates to avoid trapping into the local optimum. The local search algorithm can explore the solution space of the problem more efficiently. Static and dynamic experiments are undertaken to evaluate the performance of APGALS. The preliminary experimental results show that the adaptive parameters method and local search algorithm can improve the performance of the algorithm and the proposed APGALS is superior to the pure genetic algorithm, simulated annealing, and tabu search in terms of average fitness value and success rate in static experiment and average waiting time, number of timeout orders, and timeout accumulation in dynamic experiment.
{"title":"Optimization of O2O Food Delivery Strategy in Smart Cities","authors":"Xiangyu Kong, Guangyu Zou, Heng Qi, Jiafu Tang","doi":"10.1109/ISC255366.2022.9921961","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9921961","url":null,"abstract":"This paper studies an Online-to-Offline food delivery problem (OFDP) which can be viewed as a combination of variants of vehicle routing problems (VRPs). First, We define and model the OFDP mathematically. Then, we propose a novel adaptive parameters genetic algorithm with local search (APGALS) to solve the OFDP. The adaptive parameters method dynamically adjusts the crossover and mutation rates to avoid trapping into the local optimum. The local search algorithm can explore the solution space of the problem more efficiently. Static and dynamic experiments are undertaken to evaluate the performance of APGALS. The preliminary experimental results show that the adaptive parameters method and local search algorithm can improve the performance of the algorithm and the proposed APGALS is superior to the pure genetic algorithm, simulated annealing, and tabu search in terms of average fitness value and success rate in static experiment and average waiting time, number of timeout orders, and timeout accumulation in dynamic experiment.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121613368","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922040
Levent Görgü, M. O'Grady, E. Mangina, Gregory M. P. O'Hare
Citizen observations can strengthen regional and national risk management systems enabling geohazard risk prevention. Implementation of innovative ways following User-Centered Design (UCD) and User-Driven Development (UDD) concepts for gathering information about a geohazard via applications running on citizens' portable devices are still a novel area in citizen science. Enabling citizens to help observe and be engaged with their environment opens the opportunity to collect low-cost and considerable amounts of data in a brief amount of time. AGEO (Platform for Atlantic Geohazard Risk Management) aims to collaborate with local communities and local government authorities to encourage active participation in risk preparedness and monitoring. This paper presents the AGEO platform and mobile Citizen Observatory application. Our initial experiences and the early results of a usability evaluation survey on collecting data for eight types of hazards are presented. This will inform the formulation of recommendations for creating future citizen observatories in the disaster management domain.
{"title":"Participatory Risk Management in the Smart City","authors":"Levent Görgü, M. O'Grady, E. Mangina, Gregory M. P. O'Hare","doi":"10.1109/ISC255366.2022.9922040","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922040","url":null,"abstract":"Citizen observations can strengthen regional and national risk management systems enabling geohazard risk prevention. Implementation of innovative ways following User-Centered Design (UCD) and User-Driven Development (UDD) concepts for gathering information about a geohazard via applications running on citizens' portable devices are still a novel area in citizen science. Enabling citizens to help observe and be engaged with their environment opens the opportunity to collect low-cost and considerable amounts of data in a brief amount of time. AGEO (Platform for Atlantic Geohazard Risk Management) aims to collaborate with local communities and local government authorities to encourage active participation in risk preparedness and monitoring. This paper presents the AGEO platform and mobile Citizen Observatory application. Our initial experiences and the early results of a usability evaluation survey on collecting data for eight types of hazards are presented. This will inform the formulation of recommendations for creating future citizen observatories in the disaster management domain.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132058382","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}
Pub Date : 2022-09-26DOI: 10.1109/ISC255366.2022.9922075
J. P. J. Peixoto, D. G. Costa, Washington de J. S. da Franca Rocha, P. Portugal, F. Vasques
Among the innovative services provided by smart cities initiatives, emergencies management systems have stood out as a mean to prevent the occurrence of disasters in urban areas, detecting emergencies as soon as possible and triggering response actions. For that, such systems may rely on multiple emergencies detection units spread over a city, which will be used to detect abnormal situations and report them for further processing. Although the use of multi-sensors hardware units seems to be reasonable to detect a lot of emergency-related variables such as temperature, humidity, smoke, and toxic gases, cities may have different geographical zones concerning the potential negative impacts (risk) that an emergency may have until it is properly mitigated. Therefore, such risk associated to those zones should guide the deployment of emergencies detection units, but their computation is not straightforward and it may depend on different parameters. In this context, this paper proposes a mathematical model to compute mitigation zones in any city, taking as reference the availability of response centers retrieved from open geospatial databases, notably hospitals, fire departments, and police stations. An algorithm is defined to compute a critical index to each zone, which will be exploited to indicate the proportional number of detection units that should be allocated according to the total number of available units. Initial results for the city of Porto, Portugal, are presented, which are discussed when concerning the construction of practical emergencies management systems.
{"title":"Optimizing the deployment of multi-sensors emergencies detection units based on the presence of response centers in smart cities","authors":"J. P. J. Peixoto, D. G. Costa, Washington de J. S. da Franca Rocha, P. Portugal, F. Vasques","doi":"10.1109/ISC255366.2022.9922075","DOIUrl":"https://doi.org/10.1109/ISC255366.2022.9922075","url":null,"abstract":"Among the innovative services provided by smart cities initiatives, emergencies management systems have stood out as a mean to prevent the occurrence of disasters in urban areas, detecting emergencies as soon as possible and triggering response actions. For that, such systems may rely on multiple emergencies detection units spread over a city, which will be used to detect abnormal situations and report them for further processing. Although the use of multi-sensors hardware units seems to be reasonable to detect a lot of emergency-related variables such as temperature, humidity, smoke, and toxic gases, cities may have different geographical zones concerning the potential negative impacts (risk) that an emergency may have until it is properly mitigated. Therefore, such risk associated to those zones should guide the deployment of emergencies detection units, but their computation is not straightforward and it may depend on different parameters. In this context, this paper proposes a mathematical model to compute mitigation zones in any city, taking as reference the availability of response centers retrieved from open geospatial databases, notably hospitals, fire departments, and police stations. An algorithm is defined to compute a critical index to each zone, which will be exploited to indicate the proportional number of detection units that should be allocated according to the total number of available units. Initial results for the city of Porto, Portugal, are presented, which are discussed when concerning the construction of practical emergencies management systems.","PeriodicalId":277015,"journal":{"name":"2022 IEEE International Smart Cities Conference (ISC2)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132171220","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}
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