Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://hdl.handle.net/11449/218899 |
Resumo: | This paper describes the development of a real application using Drones over urban regions to help the authorities at epidemiological control through a disruptive solutions based on a customizable Smart & Integrated Management System (SIGI), devices and software based on the Enterprise Resource Planning (ERP) concept. Compound by management software, Drones and specific IoT devices, both referred to as sensors, the sensors collect the data of the interest areas in real time, creating a specified database. Based on the data collected from the interest areas, SIGI software has the ability to show real-time situational analysis of these areas and allows that the administrator can optimize resources (material and human) improving the efficiency of resource allocation in these areas. In addition to the development of the management software, the development of sensors to collect the information in the field and update these information to the database of the management software, are considered. The sensors will be recognized as IoT devices for the collection of meteorological data, images and command / control Drones. Initially the system will be customized, using an Artificial Intelligence tool, to collect data and identify the outbreaks of the dengue mosquito, zika and Chikungunya, nominee by risk areas. After the definition of the potential risk areas, in a complementary way, a totally customized Drone will be used to map these areas of interest, generating aerial photographs, identifying and geotagging the potential targets, which will allow the agents to identify potential mosquito breeding sites. After the identification of breeding areas, the next step will be the effective combat of the vectors, using the Drones to fly over the areas of interest, where biological defenses will be dropped over the targets to combat mosquitoes. Due some Drone flight restrictions over the cities, the whole process will be monitored by a situation room, that will be able to control the Drone remotely, access the air space controller, reads the sensors installed in the city (field), that will measure, for example, rainfall through weather stations installed in risk areas and subsequently processed by Intelligent System Integrated Management (SIGI), which will result to the information public official reflecting the situational analysis of the areas, which will enable a better management of available resources, helping the public agent, preventively in the decision making. |
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Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using DronesThis paper describes the development of a real application using Drones over urban regions to help the authorities at epidemiological control through a disruptive solutions based on a customizable Smart & Integrated Management System (SIGI), devices and software based on the Enterprise Resource Planning (ERP) concept. Compound by management software, Drones and specific IoT devices, both referred to as sensors, the sensors collect the data of the interest areas in real time, creating a specified database. Based on the data collected from the interest areas, SIGI software has the ability to show real-time situational analysis of these areas and allows that the administrator can optimize resources (material and human) improving the efficiency of resource allocation in these areas. In addition to the development of the management software, the development of sensors to collect the information in the field and update these information to the database of the management software, are considered. The sensors will be recognized as IoT devices for the collection of meteorological data, images and command / control Drones. Initially the system will be customized, using an Artificial Intelligence tool, to collect data and identify the outbreaks of the dengue mosquito, zika and Chikungunya, nominee by risk areas. After the definition of the potential risk areas, in a complementary way, a totally customized Drone will be used to map these areas of interest, generating aerial photographs, identifying and geotagging the potential targets, which will allow the agents to identify potential mosquito breeding sites. After the identification of breeding areas, the next step will be the effective combat of the vectors, using the Drones to fly over the areas of interest, where biological defenses will be dropped over the targets to combat mosquitoes. Due some Drone flight restrictions over the cities, the whole process will be monitored by a situation room, that will be able to control the Drone remotely, access the air space controller, reads the sensors installed in the city (field), that will measure, for example, rainfall through weather stations installed in risk areas and subsequently processed by Intelligent System Integrated Management (SIGI), which will result to the information public official reflecting the situational analysis of the areas, which will enable a better management of available resources, helping the public agent, preventively in the decision making.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)FINEPIBRV Inst Res & Dev, Mogi Das Cruzes, SP, BrazilBRV UAV & Flight Syst BRVANT, Mogi Das Cruzes, SP, BrazilUNESP Sao Paulo State Univ, Guaratingueta, SP, BrazilUNESP Sao Paulo State Univ, Guaratingueta, SP, BrazilFINEP: PD 2019/13442-8FINEP: 2018/10036-6IeeeIBRV Inst Res & DevBRV UAV & Flight Syst BRVANTUniversidade Estadual Paulista (UNESP)Rangel, Rodrigo KuntzFreitas Jr, Joacy L. [UNESP]Souza, Teofilo Miguel de [UNESP]IEEE2022-04-28T17:30:24Z2022-04-28T17:30:24Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject122020 Ieee Aerospace Conference (aeroconf 2020). New York: Ieee, 12 p., 2020.1095-323Xhttp://hdl.handle.net/11449/218899WOS:000681699101070Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2020 Ieee Aerospace Conference (aeroconf 2020)info:eu-repo/semantics/openAccess2024-07-01T20:12:34Zoai:repositorio.unesp.br:11449/218899Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T23:54:51.811063Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
title |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
spellingShingle |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones Rangel, Rodrigo Kuntz |
title_short |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
title_full |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
title_fullStr |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
title_full_unstemmed |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
title_sort |
Smart & Integrated Management System - Smart Cities, Epidemiological Control Tool Using Drones |
author |
Rangel, Rodrigo Kuntz |
author_facet |
Rangel, Rodrigo Kuntz Freitas Jr, Joacy L. [UNESP] Souza, Teofilo Miguel de [UNESP] IEEE |
author_role |
author |
author2 |
Freitas Jr, Joacy L. [UNESP] Souza, Teofilo Miguel de [UNESP] IEEE |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
IBRV Inst Res & Dev BRV UAV & Flight Syst BRVANT Universidade Estadual Paulista (UNESP) |
dc.contributor.author.fl_str_mv |
Rangel, Rodrigo Kuntz Freitas Jr, Joacy L. [UNESP] Souza, Teofilo Miguel de [UNESP] IEEE |
description |
This paper describes the development of a real application using Drones over urban regions to help the authorities at epidemiological control through a disruptive solutions based on a customizable Smart & Integrated Management System (SIGI), devices and software based on the Enterprise Resource Planning (ERP) concept. Compound by management software, Drones and specific IoT devices, both referred to as sensors, the sensors collect the data of the interest areas in real time, creating a specified database. Based on the data collected from the interest areas, SIGI software has the ability to show real-time situational analysis of these areas and allows that the administrator can optimize resources (material and human) improving the efficiency of resource allocation in these areas. In addition to the development of the management software, the development of sensors to collect the information in the field and update these information to the database of the management software, are considered. The sensors will be recognized as IoT devices for the collection of meteorological data, images and command / control Drones. Initially the system will be customized, using an Artificial Intelligence tool, to collect data and identify the outbreaks of the dengue mosquito, zika and Chikungunya, nominee by risk areas. After the definition of the potential risk areas, in a complementary way, a totally customized Drone will be used to map these areas of interest, generating aerial photographs, identifying and geotagging the potential targets, which will allow the agents to identify potential mosquito breeding sites. After the identification of breeding areas, the next step will be the effective combat of the vectors, using the Drones to fly over the areas of interest, where biological defenses will be dropped over the targets to combat mosquitoes. Due some Drone flight restrictions over the cities, the whole process will be monitored by a situation room, that will be able to control the Drone remotely, access the air space controller, reads the sensors installed in the city (field), that will measure, for example, rainfall through weather stations installed in risk areas and subsequently processed by Intelligent System Integrated Management (SIGI), which will result to the information public official reflecting the situational analysis of the areas, which will enable a better management of available resources, helping the public agent, preventively in the decision making. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-01-01 2022-04-28T17:30:24Z 2022-04-28T17:30:24Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
2020 Ieee Aerospace Conference (aeroconf 2020). New York: Ieee, 12 p., 2020. 1095-323X http://hdl.handle.net/11449/218899 WOS:000681699101070 |
identifier_str_mv |
2020 Ieee Aerospace Conference (aeroconf 2020). New York: Ieee, 12 p., 2020. 1095-323X WOS:000681699101070 |
url |
http://hdl.handle.net/11449/218899 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2020 Ieee Aerospace Conference (aeroconf 2020) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
12 |
dc.publisher.none.fl_str_mv |
Ieee |
publisher.none.fl_str_mv |
Ieee |
dc.source.none.fl_str_mv |
Web of Science reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
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1808129564367388672 |