J Radianti - Academia.edu (original) (raw)

Papers by J Radianti

Understanding information flows is essential to improve coordination information systems. Aims of... more Understanding information flows is essential to improve coordination information systems. Aims of such systems are typically reducing information overload and improving situational awareness. Yet, there is a lack of intuitive and easily understandable tools that help to structure and visualize the ad hoc information flows that occur during search and rescue operations. In this paper, we present the concept of such an analysis, and present findings from an indoor serious fire game. For this game, we describe the interactions of Emergency Responders (ER), including individual information (over-)load, and descriptions of content of communications. This approach therefore provides an effective way to learn about active teams, information flows, exchanged information, and overload.

Proceedings of the 17th International Conference on Enterprise Information Systems, 2015

In this paper, we present a thorough overview of the two recently developed applications in the f... more In this paper, we present a thorough overview of the two recently developed applications in the field of emergency management. The applications titled GDACSmobile and SmartRescue are using mobile app and smartphone sensors as the main functionality respectively. Furthermore, we argue the differences and similarities of both applications and highlight their strengths and weaknesses. Finally, a critical scenario for fire emergency in a music festival is designed and the applicability of the features of each application in supporting the emergency management procedure is discussed. It is also argued how the aforementioned applications can support each other during emergencies and what the potential collaboration between them can be.

2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), 2014

ABSTRACT The advanced sensors embedded in modern smartphones opens up for novel research opportun... more ABSTRACT The advanced sensors embedded in modern smartphones opens up for novel research opportunities, as for instance manifested in the field of mobile phone sensing. Most notable is perhaps research activities within human activity recognition and context-aware applications. Along a similar vein, the SmartRescue project targets monitoring of both hazard developments as well as tracking of people in a disaster, taking advantage of smartphone sensing, processing and communication capabilities. The goal is to help crisis managers and the public in early hazard detection, hazard prediction, and in the forming of risk minimizing evacuation plans when disaster strikes. In this paper we propose a novel smartphone based communication framework for disaster specific machine learning techniques that intelligently process sensor readings into useful information for the crisis responders. Core to the framework is a robust content-based publish-subscribe mechanism that allows flexible sharing of sensor data and computation results. The proposed communication platform has been tested at the proof of concept level, with several detailed features providing promising results. We also provide the initial results from the development of this platform and discuss how to enhance the platform to become a disaster monitoring system for practical use.

2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE), 2013

ABSTRACT We present an evacuation model for ships while a fire happens onboard. The model is desi... more ABSTRACT We present an evacuation model for ships while a fire happens onboard. The model is designed by utilizing Bayesian networks (BN) and then simulated in GeNIe software. In our proposed model, the most important factors that have significant influence on a rescue process and evacuation time are identified and analyzed. By applying the probability distribution of the considered factors collected from the literature including IMO, real empirical data and practical experiences, the trend of the rescue process and evacuation time can be evaluated and predicted using the proposed model. The results of this paper help understanding about possible consequences of influential factors on the security of the ship and help to avoid exceeding evacuation time during a ship fire.

2013 46th Hawaii International Conference on System Sciences, 2013

Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from va... more Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from various fields. Better understanding of this class of crowd behavior opens up for improving evacuation policies and smarter design of buildings, increasing safety. Recently, a new class of disruptive technology has appeared: Humancentered sensing which allows crowd behavior to be monitored in real-time, and provides the basis for realtime crowd control. The question then becomes: to what degree can previous crowd models incorporate this development, and what areas need further research? In this paper, we provide a survey that describes some widely used crowd models and discuss their advantages and shortages from the angle of human-centered sensing. Our review reveals important research opportunities that may contribute to an improved and more robust emergency management.

Third International Conference on Innovative Computing Technology (INTECH 2013), 2013

ABSTRACT In this paper, we model passengers' panic during a ship fire by considering its ... more ABSTRACT In this paper, we model passengers' panic during a ship fire by considering its most influential factors. The qualitative factors are quantified, allowing us to study passengers' panic in a probabilistic manner. Considering the time-varying nature of these factors, we update the state of the factors over time. We utilize a dynamic Bayesian network (DBN) to model passengers' panic, this allows us to represent probabilistic and dynamic elements. By defining several worst-case scenarios and running the simulations, we demonstrate how panic can dynamically vary from passenger to passenger with different physical (mental) conditions. Furthermore, we show how this panic can threaten passengers' health during the evacuation process. The impact of panic on the evacuation time is also investigated. The results in this paper are valuable inputs for rescue teams and marine organizations that aim to mitigate property damages and human fatalities.

International Journal of Critical Infrastructure Protection, 2009

The protection of critical infrastructure requires an understanding of the effects of change on c... more The protection of critical infrastructure requires an understanding of the effects of change on current and future safety and operations. Vulnerabilities may emerge during the rollout of updated techniques and integration of new technology with existing work practices. Managers need to understand how their decisions, often focused on economic priorities, affect the dynamics of vulnerability over time. Such understanding is

2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07), 2007

The implementation of Integrated Operations (IO) for oil and gas recovery-a real-time linkage amo... more The implementation of Integrated Operations (IO) for oil and gas recovery-a real-time linkage among platform-based facilities, onshore control centers and suppliers-is anticipated to reduce operating costs by 30%, extend the lifetime of current production fields by five years or longer and maintain Norwegian Continental Shelf production for 50-100 years. The changes in operating procedures require extensive training to ensure continued personal and environmental safety. Vulnerabilities may emerge during the rollout of updated techniques and integration of IO technology with existing work practices. We focus on user knowledge as key to successful change. A system dynamics simulation is presented that defines work process and knowledge transition. Interviews and historical records assisted in parameterizing the model. The simulation suggests that great care should be taken to facilitate and monitor the rate of knowledge maturation, even in the face of expensive implementation delays, to reduce the risk of catastrophic failure from endemic incidents. 1

The increasingly sophisticated sensors supported by modern smartphones open up novel research opp... more The increasingly sophisticated sensors supported by modern smartphones open up novel research opportunities, such as mobile phone sensing. One of the most challenging of these research areas is context-aware and activity recognition. The SmartRescue project takes advantage of smartphone sensing, processing and communication capabilities to monitor hazards and track people in a disaster. The goal is to help crisis managers and members of the public in early hazard detection, prediction, and in devising risk-minimizing evacuation plans when disaster strikes. In this paper we suggest a novel smartphone-based communication framework. It uses specific machine learning techniques that intelligently process sensor readings into useful information for the crisis responders. Core to the framework is a content-based publish-subscribe mechanism that allows flexible sharing of sensor data and computation results. We also evaluate a preliminary implementation of the platform, involving a smartphone app that reads and shares mobile phone sensor data for activity recognition.

In this paper, a new simulation model to analyze congestions in ship evacuation is introduced. To... more In this paper, a new simulation model to analyze congestions in ship evacuation is introduced. To guarantee a safe evacuation, the model considers the most important reallife factors including, but not limited to, the passengers' panic, the age or sex of the passengers, the structure of the ship. The qualitative factors have been quantized in order to compute the probability of congestion during the entire evacuation. We then utilize the dynamic Bayesian network (DBN) to predict congestion and to handle the non-stationarity of the scenario with respect to the time. Considering the worst-case scenarios and running the simulation for two groups of passengers (different in sex, age, and physical ability), we demonstrate the distinct effects of these groups on the congestion. The role of decision supports (DS), such as evacuation applications and rescue team presence is also studied. In addition, the impact of congested escape routes on the evacuation time is investigated. The results of this paper are of great importance for maritime organizations, emergency management sectors, and rescuers onboard the ships, which try to alleviate the human or property losses.

Applied Intelligence, 2014

ABSTRACT Managing the uncertainties that arise in disasters - such as a ship or building fire - c... more ABSTRACT Managing the uncertainties that arise in disasters - such as a ship or building fire - can be extremely challenging. Previous work has typically focused either on modeling crowd behavior, hazard dynamics, or targeting fully known environments. However, when a disaster strikes, uncertainties about the nature, extent and further development of the hazard is the rule rather than the exception. Additionally, crowds and hazard dynamics are both intertwined and uncertain, making evacuation planning extremely difficult. To address this challenge, we propose a novel spatio-temporal probabilistic model that integrates crowd and hazard dynamics, using ship- and building fire as proof-of-concept scenarios. The model is realized as a dynamic Bayesian network (DBN), supporting distinct kinds of crowd evacuation behavior, being based on studies of physical fire models, crowd psychology models, and corresponding flow models. Simulation results demonstrate that the DBN model allows us to track and forecast the movement of people until they escape, as the hazard develops from time step to time step. Our scheme thus opens up for novel in situ threat mapping and evacuation planning under uncertainty, with applications to emergency response.

Applied Intelligence, 2014

An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the peop... more An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when predefined escape routes are blocked by a hazard, and there is a need to rethink which escape route is safest. This paper addresses automatically finding the safest escape routes in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected personconsidering dynamic spread of fires, movability impairments caused by the hazards and faulty unreliable data. Special focus in this paper is on empirical tests for the proposed algorithms. This paper brings together the Ant Colony approach with a realistic fire dynamics simulator, and shows that the proposed solution is not only able to outperform comparable alternatives in static and dynamic environments, but also in environments with realistic spreading of fire and smoke causing fatalities. The aim of the solutions is usage by both individuals, such as from a personal smartphone of

Lecture Notes in Computer Science, 2013

An emergency requiring evacuation is a chaotic event filled with uncertainties both for the peopl... more An emergency requiring evacuation is a chaotic event filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when a predefined escape route is blocked by a hazard, and there is a need to rethink which escape route is safest. This paper addresses automatically finding the safest escape route in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected personconsidering both dynamic spread of hazards and congestion avoidance. The solution can be used both on an individual bases, such as from a personal smart phone of one of the evacuees, or from a remote location by emergency personnel trying to assist large groups.

Workshop for Information Security and Privacy

WISP'07 Montreal Canada Using a Mixed Data Collection Strategy to Uncover Vulnerability Blac... more WISP'07 Montreal Canada Using a Mixed Data Collection Strategy to Uncover Vulnerability Black Markets Jaziar Radianti University of Agder jaziar.radianti@uia.no Eliot Rich University at Albany e.rich@albany.edu Jose. J. Gonzalez University of Agder jose.j.gonzalez@uia.no ...

Proceedings of the the 27th …, 2009

The discovery and management of software vulnerabilities after a product is released to the publi... more The discovery and management of software vulnerabilities after a product is released to the public is an important element of improving software quality and stability. The discovery of vulnerabilities enables exploitation and stimulates the development of patches or other protections, ...

International Journal of Machine Learning and Computing, 2014

Understanding information flows is essential to improve coordination information systems. Aims of... more Understanding information flows is essential to improve coordination information systems. Aims of such systems are typically reducing information overload and improving situational awareness. Yet, there is a lack of intuitive and easily understandable tools that help to structure and visualize the ad hoc information flows that occur during search and rescue operations. In this paper, we present the concept of such an analysis, and present findings from an indoor serious fire game. For this game, we describe the interactions of Emergency Responders (ER), including individual information (over-)load, and descriptions of content of communications. This approach therefore provides an effective way to learn about active teams, information flows, exchanged information, and overload.

Proceedings of the 17th International Conference on Enterprise Information Systems, 2015

In this paper, we present a thorough overview of the two recently developed applications in the f... more In this paper, we present a thorough overview of the two recently developed applications in the field of emergency management. The applications titled GDACSmobile and SmartRescue are using mobile app and smartphone sensors as the main functionality respectively. Furthermore, we argue the differences and similarities of both applications and highlight their strengths and weaknesses. Finally, a critical scenario for fire emergency in a music festival is designed and the applicability of the features of each application in supporting the emergency management procedure is discussed. It is also argued how the aforementioned applications can support each other during emergencies and what the potential collaboration between them can be.

2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), 2014

ABSTRACT The advanced sensors embedded in modern smartphones opens up for novel research opportun... more ABSTRACT The advanced sensors embedded in modern smartphones opens up for novel research opportunities, as for instance manifested in the field of mobile phone sensing. Most notable is perhaps research activities within human activity recognition and context-aware applications. Along a similar vein, the SmartRescue project targets monitoring of both hazard developments as well as tracking of people in a disaster, taking advantage of smartphone sensing, processing and communication capabilities. The goal is to help crisis managers and the public in early hazard detection, hazard prediction, and in the forming of risk minimizing evacuation plans when disaster strikes. In this paper we propose a novel smartphone based communication framework for disaster specific machine learning techniques that intelligently process sensor readings into useful information for the crisis responders. Core to the framework is a robust content-based publish-subscribe mechanism that allows flexible sharing of sensor data and computation results. The proposed communication platform has been tested at the proof of concept level, with several detailed features providing promising results. We also provide the initial results from the development of this platform and discuss how to enhance the platform to become a disaster monitoring system for practical use.

2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE), 2013

ABSTRACT We present an evacuation model for ships while a fire happens onboard. The model is desi... more ABSTRACT We present an evacuation model for ships while a fire happens onboard. The model is designed by utilizing Bayesian networks (BN) and then simulated in GeNIe software. In our proposed model, the most important factors that have significant influence on a rescue process and evacuation time are identified and analyzed. By applying the probability distribution of the considered factors collected from the literature including IMO, real empirical data and practical experiences, the trend of the rescue process and evacuation time can be evaluated and predicted using the proposed model. The results of this paper help understanding about possible consequences of influential factors on the security of the ship and help to avoid exceeding evacuation time during a ship fire.

2013 46th Hawaii International Conference on System Sciences, 2013

Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from va... more Emergency evacuation of crowds is a fascinating phenomenon that has attracted researchers from various fields. Better understanding of this class of crowd behavior opens up for improving evacuation policies and smarter design of buildings, increasing safety. Recently, a new class of disruptive technology has appeared: Humancentered sensing which allows crowd behavior to be monitored in real-time, and provides the basis for realtime crowd control. The question then becomes: to what degree can previous crowd models incorporate this development, and what areas need further research? In this paper, we provide a survey that describes some widely used crowd models and discuss their advantages and shortages from the angle of human-centered sensing. Our review reveals important research opportunities that may contribute to an improved and more robust emergency management.

Third International Conference on Innovative Computing Technology (INTECH 2013), 2013

ABSTRACT In this paper, we model passengers' panic during a ship fire by considering its ... more ABSTRACT In this paper, we model passengers' panic during a ship fire by considering its most influential factors. The qualitative factors are quantified, allowing us to study passengers' panic in a probabilistic manner. Considering the time-varying nature of these factors, we update the state of the factors over time. We utilize a dynamic Bayesian network (DBN) to model passengers' panic, this allows us to represent probabilistic and dynamic elements. By defining several worst-case scenarios and running the simulations, we demonstrate how panic can dynamically vary from passenger to passenger with different physical (mental) conditions. Furthermore, we show how this panic can threaten passengers' health during the evacuation process. The impact of panic on the evacuation time is also investigated. The results in this paper are valuable inputs for rescue teams and marine organizations that aim to mitigate property damages and human fatalities.

International Journal of Critical Infrastructure Protection, 2009

The protection of critical infrastructure requires an understanding of the effects of change on c... more The protection of critical infrastructure requires an understanding of the effects of change on current and future safety and operations. Vulnerabilities may emerge during the rollout of updated techniques and integration of new technology with existing work practices. Managers need to understand how their decisions, often focused on economic priorities, affect the dynamics of vulnerability over time. Such understanding is

2007 40th Annual Hawaii International Conference on System Sciences (HICSS'07), 2007

The implementation of Integrated Operations (IO) for oil and gas recovery-a real-time linkage amo... more The implementation of Integrated Operations (IO) for oil and gas recovery-a real-time linkage among platform-based facilities, onshore control centers and suppliers-is anticipated to reduce operating costs by 30%, extend the lifetime of current production fields by five years or longer and maintain Norwegian Continental Shelf production for 50-100 years. The changes in operating procedures require extensive training to ensure continued personal and environmental safety. Vulnerabilities may emerge during the rollout of updated techniques and integration of IO technology with existing work practices. We focus on user knowledge as key to successful change. A system dynamics simulation is presented that defines work process and knowledge transition. Interviews and historical records assisted in parameterizing the model. The simulation suggests that great care should be taken to facilitate and monitor the rate of knowledge maturation, even in the face of expensive implementation delays, to reduce the risk of catastrophic failure from endemic incidents. 1

The increasingly sophisticated sensors supported by modern smartphones open up novel research opp... more The increasingly sophisticated sensors supported by modern smartphones open up novel research opportunities, such as mobile phone sensing. One of the most challenging of these research areas is context-aware and activity recognition. The SmartRescue project takes advantage of smartphone sensing, processing and communication capabilities to monitor hazards and track people in a disaster. The goal is to help crisis managers and members of the public in early hazard detection, prediction, and in devising risk-minimizing evacuation plans when disaster strikes. In this paper we suggest a novel smartphone-based communication framework. It uses specific machine learning techniques that intelligently process sensor readings into useful information for the crisis responders. Core to the framework is a content-based publish-subscribe mechanism that allows flexible sharing of sensor data and computation results. We also evaluate a preliminary implementation of the platform, involving a smartphone app that reads and shares mobile phone sensor data for activity recognition.

In this paper, a new simulation model to analyze congestions in ship evacuation is introduced. To... more In this paper, a new simulation model to analyze congestions in ship evacuation is introduced. To guarantee a safe evacuation, the model considers the most important reallife factors including, but not limited to, the passengers' panic, the age or sex of the passengers, the structure of the ship. The qualitative factors have been quantized in order to compute the probability of congestion during the entire evacuation. We then utilize the dynamic Bayesian network (DBN) to predict congestion and to handle the non-stationarity of the scenario with respect to the time. Considering the worst-case scenarios and running the simulation for two groups of passengers (different in sex, age, and physical ability), we demonstrate the distinct effects of these groups on the congestion. The role of decision supports (DS), such as evacuation applications and rescue team presence is also studied. In addition, the impact of congested escape routes on the evacuation time is investigated. The results of this paper are of great importance for maritime organizations, emergency management sectors, and rescuers onboard the ships, which try to alleviate the human or property losses.

Applied Intelligence, 2014

ABSTRACT Managing the uncertainties that arise in disasters - such as a ship or building fire - c... more ABSTRACT Managing the uncertainties that arise in disasters - such as a ship or building fire - can be extremely challenging. Previous work has typically focused either on modeling crowd behavior, hazard dynamics, or targeting fully known environments. However, when a disaster strikes, uncertainties about the nature, extent and further development of the hazard is the rule rather than the exception. Additionally, crowds and hazard dynamics are both intertwined and uncertain, making evacuation planning extremely difficult. To address this challenge, we propose a novel spatio-temporal probabilistic model that integrates crowd and hazard dynamics, using ship- and building fire as proof-of-concept scenarios. The model is realized as a dynamic Bayesian network (DBN), supporting distinct kinds of crowd evacuation behavior, being based on studies of physical fire models, crowd psychology models, and corresponding flow models. Simulation results demonstrate that the DBN model allows us to track and forecast the movement of people until they escape, as the hazard develops from time step to time step. Our scheme thus opens up for novel in situ threat mapping and evacuation planning under uncertainty, with applications to emergency response.

Applied Intelligence, 2014

An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the peop... more An emergency requiring evacuation is a chaotic event, filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when predefined escape routes are blocked by a hazard, and there is a need to rethink which escape route is safest. This paper addresses automatically finding the safest escape routes in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected personconsidering dynamic spread of fires, movability impairments caused by the hazards and faulty unreliable data. Special focus in this paper is on empirical tests for the proposed algorithms. This paper brings together the Ant Colony approach with a realistic fire dynamics simulator, and shows that the proposed solution is not only able to outperform comparable alternatives in static and dynamic environments, but also in environments with realistic spreading of fire and smoke causing fatalities. The aim of the solutions is usage by both individuals, such as from a personal smartphone of

Lecture Notes in Computer Science, 2013

An emergency requiring evacuation is a chaotic event filled with uncertainties both for the peopl... more An emergency requiring evacuation is a chaotic event filled with uncertainties both for the people affected and rescuers. The evacuees are often left to themselves for navigation to the escape area. The chaotic situation increases when a predefined escape route is blocked by a hazard, and there is a need to rethink which escape route is safest. This paper addresses automatically finding the safest escape route in emergency situations in large buildings or ships with imperfect knowledge of the hazards. The proposed solution, based on Ant Colony Optimisation, suggests a near optimal escape plan for every affected personconsidering both dynamic spread of hazards and congestion avoidance. The solution can be used both on an individual bases, such as from a personal smart phone of one of the evacuees, or from a remote location by emergency personnel trying to assist large groups.

Workshop for Information Security and Privacy

WISP'07 Montreal Canada Using a Mixed Data Collection Strategy to Uncover Vulnerability Blac... more WISP'07 Montreal Canada Using a Mixed Data Collection Strategy to Uncover Vulnerability Black Markets Jaziar Radianti University of Agder jaziar.radianti@uia.no Eliot Rich University at Albany e.rich@albany.edu Jose. J. Gonzalez University of Agder jose.j.gonzalez@uia.no ...

Proceedings of the the 27th …, 2009

The discovery and management of software vulnerabilities after a product is released to the publi... more The discovery and management of software vulnerabilities after a product is released to the public is an important element of improving software quality and stability. The discovery of vulnerabilities enables exploitation and stimulates the development of patches or other protections, ...

International Journal of Machine Learning and Computing, 2014