Improving public safety at fingertips: A smart city experience

2016 ◽  
Author(s):  
Marcel Mendonca ◽  
Bruno Moreira ◽  
Jazon Coelho ◽  
Nelio Cacho ◽  
Frederico Lopes ◽  
...  
Keyword(s):  
Smart City ◽  
Public Safety

scholarly journals Challenges and Opportunities of Crowdsourcing and Participatory Planning in Developing Infrastructure Systems of Smart Cities

2018 ◽  
Vol 3 (4) ◽  
pp. 51 ◽  
Author(s):  
Parul Srivastava ◽  
Ali Mostafavi
Keyword(s):  
Disaster Management ◽  
Smart City ◽  
Public Safety ◽  
Smart Cities ◽  
Participatory Planning ◽  
Systemic Review ◽  
Infrastructure Systems ◽  
Challenges And Opportunities ◽  
System Characteristics ◽  
Environment Disaster

The concept of Smart City aims to provide its citizens with infrastructure systems that make cities safer and more livable. One of the methods for doing so is collecting data from the crowd itself—termed crowdsourcing—and incorporating their ideas to improve the existing facilities, as well as build new ones to cater to their arising needs. This paper aims to inspect the attributes that govern crowdsourcing, evaluating its feasibility in attaining solutions in the present scenario. A systemic review of the existing literature on crowdsourcing platforms was conducted and major findings have been summarized adequately. The areas of environment, disaster management, public safety, innovation, transportation and health have been explored in connection to the existing crowdsourcing platforms and selected examples have been mentioned. Next, the attributes that affect crowdsourcing have been discussed in detail under three broad categories: (1) human characteristics; (2) data characteristics and (3) system characteristics. In the end, some recommendations for improvement in the implementation of the crowdsourcing platforms have been proposed for their enhanced applicability and effectiveness.

‘Smart’ crime prevention? Digitization and racialized crime control in a Smart City

2020 ◽  
pp. 136248062097270
Author(s):  
Pat O’Malley ◽  
Gavin JD Smith
Keyword(s):  
Criminal Justice ◽  
Crime Prevention ◽  
Smart City ◽  
Public Safety ◽  
Crime Control ◽  
Aboriginal People ◽  
Smart Cities ◽  
Led Lighting ◽  
Visible Minorities ◽  
Smart Technologies

As part of the global Smart Cities movement, the Switching on Darwin programme foregrounds digitally enhanced government and urbanism. While promoting its environmental and democratizing potential, software-enhanced CCTV, LED lighting and geofencing were among the first components rolled out. In practice, these technologies will impact adversely on Aboriginal people, already disproportionately targeted by criminal justice processes. By integrating multiple ‘smart’ technologies with ‘public safety’ agendas, such Smart City developments provide the potential for intensified criminalization of visible minorities.

scholarly journals IOT Smart City: Introduction and Challenges

2019 ◽  
Vol 8 (3) ◽  
pp. 3484-3487 ◽  
Keyword(s):  
Water Supply ◽  
Public Transportation ◽  
Traffic Congestion ◽  
Smart City ◽  
Public Safety ◽  
Treatment Plant ◽  
Privacy And Security ◽  
Safety Issues ◽  
The World ◽  
Innovative Solution

In an IOT based smart city, the most astonishing and, the most reflective component would be a much more efficient water supply. This kind of water supply treatment plant that would be established will be a much more advanced version of the already existing kinds. This water supply would help many people across the globe to get access to clean, drinking water and sanitation. Also, in such a city there would be provided an innovative solution to the huge traffic congestion being faced these days that leads to delays in reaching to work, rash driving and results in huge chaos and accidents. Thus, it would be great to kept in mind to provide a mid-way out to deal with these traffic issues in a more reliable and efficient way. We would provide a more reliable public transportation. Public transportation these days are the most relied means of conveyance for people living in all parts of the world. Thus, we would build up a more reliable public transport structure that would be effortless. This would minimize the deals, difficulties and would maximize the ease for the travelers. The next thing would be to make energy efficient buildings that will aim at minimizing the wastage of energy of the entire community. These buildings would run on least amount of possible energy (for e.g. solar energy) resulting in minimum loss. Safety is a major concern these days. There are lot of safety issues popping up in all parts of the world. Thus, in our model, we would provide an improved public safety that links back to the infrastructure, buildings, lifts, escalators, elevators, public transportation etc. Thus, with improved public safety, all these factors would be procured. However, with all these aims being enforced in the city, there would come up a lot of challenges that would be needed to countered. The system software that would be the base of framework of this IOT based smart city, would be vulnerable to hacks, system failures i.e. trojans, malware and viruses. This would result in privacy and security concerns but obvious, and also difficulties in interoperability, but suitable specific would be procured to counter these issues as well.

scholarly journals Real-time Big Data Analytics Framework with Data Blending Approach for Multiple Data sources in Smart City Applications

2020 ◽  
Vol 21 (4) ◽  
pp. 611-623
Author(s):  
Manjunatha S ◽  
Annappa B
Keyword(s):  
Real Time ◽  
Smart City ◽  
Data Analytics ◽  
Public Safety ◽  
Big Data Analytics ◽  
Data Sources ◽  
Data Driven ◽  
The Public ◽  
Multiple Data Sources ◽  
Multiple Data

Advancement in Information Communication Technology (ICT) and the Internet of Things (IoT) has to lead tothe continuous generation of a large amount of data. Smart city projects are being implemented in various parts of the world where analysis of public data helps in providing a better quality of life. Data analytics plays a vital role in many such data-driven applications. Real-time analytics for finding valuable insights at the right time using smart city data is crucial in making appropriate decisions for city administration. It is essential to use multiple data sources as input for the analysis to achieve better and more accurate data-driven solutions. It helps in finding more accurate solutions and making appropriate decisions. Public safety is one of the major concerns in any smart city project in which real-time analytics is much useful in the early detection of valuable data patterns. It is crucial to find early predictions of crime-related incidents and generating emergency alerts for making appropriate decisions to provide security to the people and safety of the city infrastructure. This paper discusses the proposed real-time big data analytics framework with data blending approach using multiple data sources for smart city applications. Analytics using multiple data sources for a specific data-driven solution helps in finding more data patterns, which in turn increases the accuracy of analytics results. The data preprocessing phase is a challenging task in data analytics when data being ingested continuously in real-time into the analytics system. The proposed system helps in the preprocessing of real-time data with data blending of multiple data sources used in the analytics. The proposed framework is beneficial when data from multiple sources are ingested in real-time as input data and is also flexible to use any additional data source of interest. The experimental work carried out with the proposed framework using multiple data sources to find the crime-related insights in real-time helps the public safety solutions in the smart city. The experimental outcome shows that there is a significant increase in the number of identified useful data patterns as the number of data sources increases. A real-time based emergency alert system to help the public safety solution is implementedusing a machine learning-based classification algorithm with the proposed framework. The experiment is carried out with different classification algorithms, and the results show that Naive Bayes classification  performs better in generating emergency alerts.

scholarly journals To Smart City: Public Safety Network Design for Emergency

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 1451-1460 ◽  
Author(s):  
Shuo Wan ◽  
Jiaxun Lu ◽  
Pingyi Fan ◽  
Khaled B. Letaief
Keyword(s):  
Network Design ◽  
Smart City ◽  
Public Safety

scholarly journals Corrigendum on: Big Data and development of smart city: System architecture and practical public safety example [Serb. Jour. of Elect. Eng., Vol. 17, No. 3, Oct. 2020, pp. 337 - 355]

2021 ◽  
Vol 18 (1) ◽  
pp. 137-137
Author(s):  
E Editorial
Keyword(s):  
Big Data ◽  
System Architecture ◽  
Smart City ◽  
Public Safety ◽  
The Third ◽  
City System ◽  
Font Color

The authors of the paper entitled "Big Data and Development of Smart City: System Architecture and Practical Public Safety Example", Mirko Simic, Miroslav Peric, Ilija Popadic, Dragana Peric, Milos Pavlovic, Miljan Vucetic and Milos S. Stankovic, informed the Editor about the error in the position of the author Miljan Vucetic, who should be at the third position. The authors have requested for this error to be corrected. Therefore, the journal is publishing this Corrigendum. The authors of this article should be listed as follows: Mirko Simic, Miroslav Peric, Miljan Vucetic, Ilija Popadic, Dragana Peric, Milos Pavlovic, Milos Stankovic. <br><br><font color="red"><b> Link to the corrected article <u><a href="http://dx.doi.org/10.2298/SJEE2003337S">10.2298/SJEE2003337S</a></b></u>

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