Improving fire services using spatio-temporal analysis: Fire incidents in manila

Balahadia, Francis F.; Trillanes, Arlene O.

doi:10.1109/tenconspring.2017.8070013

Cited by 10 publications

(8 citation statements)

References 8 publications

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“…Therefore, regional fire risk analysis can provide fire departments better decision support about fire inspection and fire station planning. [3][4][5] There have been many studies on analyzing fire risk. Fire risk assessment can be divided into quantitative assessment, qualitative assessment, and semiquantitative assessment.…”

Section: Discussionmentioning

confidence: 99%

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Generalized analysis of regional fire risk using data visualization of incidents

Liu

Fan

2019

Fire and Materials

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Summary Fire has been a worldwide disaster, and it is important to analyze regional fire risk for better fire prevention. Regional fire risk can be generally analyzed by using data visualization of fire incidents. A dataset of 20 622 fire incidents in Changsha City of China from 2011 to 2017 was processed and filtered as the origin risk points. Then, a generalized risk model (GRM) was established for calculating fire risk values of anywhere in Changsha. By using JavaScript and HTML5, the generalized fire risk graphics were drawn based on mapping different fire risk values with different colors. For visualizing fire incidents, the inner and outer generalization radiuses of the origin risk point were set to be 1 (110 m) and 10 (1100 m), respectively. It was found that the high and medium fire risk areas were mainly distributed in urban areas and market towns, especially in central city. The spatial distribution characteristics of fire risk of different time ranges and different causes were significantly varied. The results can provide guidance of fire prevention for the fire department in Changsha. Other cities' regional fire risk and even other types of disaster risk can also be generally analyzed using GRM.

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Section: Discussionmentioning

confidence: 99%

“…Fire service resourcing and planning are usually carried out according to administrative area around the world. Therefore, regional fire risk analysis can provide fire departments better decision support about fire inspection and fire station planning …”

Section: Introductionmentioning

confidence: 99%

Generalized analysis of regional fire risk using data visualization of incidents

Liu

Fan

2019

Fire and Materials

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“…In 2016, over 700 fire incidents were recorded in the city resulting in damage worth more than 130 million pesos. These findings bring to fore the importance of raising awareness and providing education related to fire prevention [2].…”

Section: Introductionmentioning

confidence: 88%

“…It was estimated cost was due to losses from fire accidents is approximately one percent of global Gross Domestic Product per annum, according to World Fire Statistics. It was recorded that most number of occurrences are in (NCR) National Capital Region from a total of 883 fires and 824 fire-related casualties were reported from 2010 to 2012 in the Philippines [2]. Based on records, a total of 2,316 fire incidents was reported from 2011 to 2014.…”

Section: Introductionmentioning

confidence: 99%

NotiPoy: Early Notification of Detected Fire Using Image Processing Applying Convolutional Neural Network

Nicolas-Mindoro¹

2019

IJATCSE

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Fire incident is one of the most common undesirable events that cause damages toward houses and human. It can start anytime and anywhere without any prior hint when it would happen. With the cause it brings, the implementation of a device capable of detecting and providing notification is necessary. This study presents the method of early-stage fire-flame detection utilizing image processing integrated with the Android application for emergency notification. The proposed system utilized the image processing applying Convolutional Neural Network (CNN) integrated with mobile app as early notification to the end user. After executing 3999 iterations of 210 images are used for testing to get the Train Accuracy (how accurate the training is) and Cross entropy (how far is the prediction of the actual result), it resulted to 100% trained accuracy and 96% validation. The test evaluation accuracy result was 99% using a cached file of 210, it means that expect the model to perform ~99% accuracy on the new data. From the test that has been done, the proposed system was able to capture the fire flame images and send necessary notification real time. The test results show the captured actual images and the information sent to the end user. The summary test results verified that all gathered data was higher than 90% to be able to send notification. The android app used to show both the pre-investigation information useful for the house owner and BFP personnel.

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“…In the city of Manila, the Philippines, Balahadia and Trillanes 37 found that electrical faults were a major cause of fire incidents. The rate of fire events increases significantly during the warm months of the year.…”

Section: Introductionmentioning

confidence: 99%

An analysis of Spatio–temporal patterns of fires in an Iranian city

Mohammadi

Shahparvari

Kiani

et al. 2022

Indoor and Built Environment

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Exploring Spatio–temporal patterns of fire incidents provides important information to help develop strategies to prevent and mitigate fire risk based on geographical knowledge. This study aims to map and analyse the Spatio–temporal patterns of urban fire incidents. Fire incident data were obtained from Ardabil Municipality Fire Department and Emergency Services and analysed using radial shape charts, kernel density estimation and average nearest neighbour to quantify spatial and Spatio–temporal patterns of fires. The results show that the Spatio–temporal fire patterns vary, depending on time, their types and causes. Interestingly, results indicate that fires are most likely to occur on Tuesdays and Thursdays and during summer. The study provides evidence to enhance decision-making on resource allocation in terms of establishing new fire stations and deploying an additional workforce to more vulnerable localities, or to formulate prevention strategies, such as education campaigns, to mitigate fire risk.

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Improving fire services using spatio-temporal analysis: Fire incidents in manila

Cited by 10 publications

References 8 publications

Generalized analysis of regional fire risk using data visualization of incidents

Generalized analysis of regional fire risk using data visualization of incidents

NotiPoy: Early Notification of Detected Fire Using Image Processing Applying Convolutional Neural Network

An analysis of Spatio–temporal patterns of fires in an Iranian city

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