An Integrated Approach for Post-Disaster Flood Management Via the Use of Cutting-Edge Technologies and UAVs: A Review

<p>Every year disasters affect hundreds of millions of people, causing damage that can take months or years to recover from. The reality of carrying out the processes of reconstruction and recreating functionality is a complex and difficult task; too often it is measured in a time period of several years. The issue to be addressed through this research is the response of the built (or rebuilt) environment to the requirements of people who have been displaced following a major disaster. This thesis develops a building typology and process that can adapt to the changing requirements of the stages of the redevelopment process in a post‐disaster scenario. The research focuses on natural disasters, more vulnerable populations and regions and specifically on housing reconstruction. It explores the idea of a solution that can be applied widely, to many different climates and contexts; the research question then amounts to ‘can a solution be created that can ‘evolve’ to meet the needs at each stage of a post disaster reconstruction scenario?’ The thesis explores existing post‐disaster response and reconstruction models and discusses the focuses and priorities of each. The requirements of displaced people are studied, in terms of response by the built environment, and the benefits of staged development versus end product discussed. The roles that major groups, such as local authorities and NGOs, play in orchestrating the reconstruction process are discussed as well as the important, and sometimes overlooked, role that those affected by the disaster may have. The discussion and research then informs the design proposal. Four sites are selected and used as parameters for developing the built response to the first stage of reconstruction. The selected sites are then used to show how a generic shelter may first be adapted to be suitable for a specific climate and context and then how they may be added to and grown to become permanent and suitable housing for the displaced people. The staged redevelopment process from a partially generic emergency deployment presented in this thesis can provide a solution, or framework for a solution, to many of the problems raised by the research and here, but it cannot be a solution by itself; architecture or design in post‐disaster scenarios must be supported and driven heavily by planning and management from local, national and international sources to be successful and fully realised.</p>

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Experience, Data-Driven and Artificial Intelligence in Social (Fire) and Chemical Technology

Edelweiss Chemical Science Journal ◽

10.33805/2641.7383.114 ◽

2019 ◽

pp. 45-46

Author(s):

Takashiro Akitsu ◽

Yuika Onami

Keyword(s):

Artificial Intelligence ◽

Fire Technology ◽

Disaster Response ◽

Data Driven ◽

Disaster Prevention ◽

Emergency Situations ◽

Prevention Activities ◽

In Fire ◽

Post Disaster ◽

Disaster Prediction

“Realization of society 5.0 in fire and disaster prevention activities” is one of intensive goals of Japanese government developing fire technology [1]. Improvement of new equipment and materials for disaster response utilizing AI and ICT should be developed according to social requirements. Efforts to predict earthquake, pour, flood, etc. through AI analysis of data collected from past disasters must continue. In parallel with such elaboration of disaster prediction, it is necessary to proceed with preparations for prompt and accurate provision of disaster information during emergency situations and support for rebuilding lives post disaster.

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Experience, Data-Driven and Artificial Intelligence in Social (Fire) and Chemical Technology

Edelweiss Chemical Science Journal ◽

10.33805/2641-7383.114 ◽

2019 ◽

pp. 45-46

Author(s):

Takashiro Akitsu ◽

Yuika Onami

Keyword(s):

Artificial Intelligence ◽

Fire Technology ◽

Disaster Response ◽

Data Driven ◽

Disaster Prevention ◽

Emergency Situations ◽

Prevention Activities ◽

In Fire ◽

Post Disaster ◽

Disaster Prediction

“Realization of society 5.0 in fire and disaster prevention activities” is one of intensive goals of Japanese government developing fire technology [1]. Improvement of new equipment and materials for disaster response utilizing AI and ICT should be developed according to social requirements. Efforts to predict earthquake, pour, flood, etc. through AI analysis of data collected from past disasters must continue. In parallel with such elaboration of disaster prediction, it is necessary to proceed with preparations for prompt and accurate provision of disaster information during emergency situations and support for rebuilding lives post disaster.

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Evolution and Recovery: Adaptable Housing Reconstruction in Post Disaster Scenarios

10.26686/wgtn.16992904 ◽

2021 ◽

Author(s):

◽

Liam Shearer

Keyword(s):

Disaster Response ◽

Research Question ◽

Reconstruction Process ◽

Major Disaster ◽

Building Typology ◽

Displaced People ◽

Housing Reconstruction ◽

Disaster Scenario ◽

Design Proposal ◽

Post Disaster

<p>Every year disasters affect hundreds of millions of people, causing damage that can take months or years to recover from. The reality of carrying out the processes of reconstruction and recreating functionality is a complex and difficult task; too often it is measured in a time period of several years. The issue to be addressed through this research is the response of the built (or rebuilt) environment to the requirements of people who have been displaced following a major disaster. This thesis develops a building typology and process that can adapt to the changing requirements of the stages of the redevelopment process in a post‐disaster scenario. The research focuses on natural disasters, more vulnerable populations and regions and specifically on housing reconstruction. It explores the idea of a solution that can be applied widely, to many different climates and contexts; the research question then amounts to ‘can a solution be created that can ‘evolve’ to meet the needs at each stage of a post disaster reconstruction scenario?’ The thesis explores existing post‐disaster response and reconstruction models and discusses the focuses and priorities of each. The requirements of displaced people are studied, in terms of response by the built environment, and the benefits of staged development versus end product discussed. The roles that major groups, such as local authorities and NGOs, play in orchestrating the reconstruction process are discussed as well as the important, and sometimes overlooked, role that those affected by the disaster may have. The discussion and research then informs the design proposal. Four sites are selected and used as parameters for developing the built response to the first stage of reconstruction. The selected sites are then used to show how a generic shelter may first be adapted to be suitable for a specific climate and context and then how they may be added to and grown to become permanent and suitable housing for the displaced people. The staged redevelopment process from a partially generic emergency deployment presented in this thesis can provide a solution, or framework for a solution, to many of the problems raised by the research and here, but it cannot be a solution by itself; architecture or design in post‐disaster scenarios must be supported and driven heavily by planning and management from local, national and international sources to be successful and fully realised.</p>

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A Study of Automatic Judgment of Food Color and Cooking Conditions with Artificial Intelligence Technology

Processes ◽

10.3390/pr9071128 ◽

2021 ◽

Vol 9 (7) ◽

pp. 1128

Author(s):

Chern-Sheng Lin ◽

Yu-Ching Pan ◽

Yu-Xin Kuo ◽

Ching-Kun Chen ◽

Chuen-Lin Tien

Keyword(s):

Artificial Intelligence ◽

Image Processing ◽

Color Space ◽

Color Difference ◽

Color Space Conversion ◽

Before And After ◽

Artificial Intelligence Technology ◽

Artificial Intelligence Algorithm ◽

Time Image ◽

Cooking Conditions

In this study, the machine vision and artificial intelligence algorithms were used to rapidly check the degree of cooking of foods and avoid the over-cooking of foods. Using a smart induction cooker for heating, the image processing program automatically recognizes the color of the food before and after cooking. The new cooking parameters were used to identify the cooking conditions of the food when it is undercooked, cooked, and overcooked. In the research, the camera was used in combination with the software for development, and the real-time image processing technology was used to obtain the information of the color of the food, and through calculation parameters, the cooking status of the food was monitored. In the second year, using the color space conversion, a novel algorithm, and artificial intelligence, the foreground segmentation was used to separate the vegetables from the background, and the cooking ripeness, cooking unevenness, oil glossiness, and sauce absorption were calculated. The image color difference and the distribution were used to judge the cooking conditions of the food, so that the cooking system can identify whether or not to adopt partial tumbling, or to end a cooking operation. A novel artificial intelligence algorithm is used in the relative field, and the error rate can be reduced to 3%. This work will significantly help researchers working in the advanced cooking devices.

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