Internet of things for disaster management: state-of-the-art and prospects

Disastrous events are cordially involved with the momentum of nature. As such mishaps have been showing off own mastery, situations have gone beyond the control of human resistive mechanisms far ago. Fortunately, several technologies are in service to gain affirmative knowledge and analysis of a disaster's occurrence. Recently, Internet of Things (IoT) paradigm has opened a promising door toward catering of multitude problems related to agriculture, industry, security, and medicine due to its attractive features, such as heterogeneity, interoperability, light-weight, and flexibility. This paper surveys existing approaches to encounter the relevant issues with disasters, such as early warning, notification, data analytics, knowledge aggregation, remote monitoring, real-time analytics, and victim localization. Simultaneous interventions with IoT are also given utmost importance while presenting these facts. A comprehensive discussion on the state-of-the-art scenarios to handle disastrous events is presented. Furthermore, IoT-supported protocols and market-ready deployable products are summarized to address these issues. Finally, this survey highlights open challenges and research trends in IoT-enabled disaster management systems. © 2013 IEEE

Algorithms leveraging smartphone sensing for analyzing explosion events

The increasing frequency of explosive disasters throughout the world in recent years have created a clear need for the systems to monitor for them continuously to improve the post-disaster emergency events such as rescue and recovery operations. Disasters both man-made and natural are unfortunate and not preferred, however monitoring them may be a lifesaving phenomenon in emergency scenarios. Dedicated sensors deployed in the public places and their associated networks to monitor such events may be inadequate and must be complemented for making the monitoring more pervasive and effective. In the recent past, modern smartphones with significant processing, networking and storage capabilities have become a rich source of mobile infrastructure empowering participatory sensing to address many problems in the area of pervasive computing. In the work presented in this dissertation, smartphone sensed data during disastrous scenarios is extensively studied, analyzed and algorithms were built for participatory sensing to address the problems, specifically in the context of Explosion -- Events which are of interest to the current study. This work presents description of the systems for assisting people by detecting, ranging and estimating intensity of the explosion events leveraging multi-modal smartphone sensors. This work also presents various challenges and opportunities in utilizing the capabilities of the sensors in smartphone for building such systems along with practical applications, limitations and future directions --Abstract, page iii

Pedestrian Counting Based on Piezoelectric Vibration Sensor

Pedestrian counting has attracted much interest of the academic and industry communities for its widespread application in many real-world scenarios. While many recent studies have focused on computer vision-based solutions for the problem, the deployment of cameras brings up concerns about privacy invasion. This paper proposes a novel indoor pedestrian counting approach, based on footstep-induced structural vibration signals with piezoelectric sensors. The approach is privacy-protecting because no audio or video data is acquired. Our approach analyzes the space-differential features from the vibration signals caused by pedestrian footsteps and outputs the number of pedestrians. The proposed approach supports multiple pedestrians walking together with signal mixture. Moreover, it makes no requirement about the number of groups of walking people in the detection area. The experimental results show that the averaged F1-score of our approach is over 0.98, which is better than the vibration signal-based state-of-the-art methods.Peer reviewe

Smart Monitoring and Control in the Future Internet of Things

The Internet of Things (IoT) and related technologies have the promise of realizing pervasive and smart applications which, in turn, have the potential of improving the quality of life of people living in a connected world. According to the IoT vision, all things can cooperate amongst themselves and be managed from anywhere via the Internet, allowing tight integration between the physical and cyber worlds and thus improving efficiency, promoting usability, and opening up new application opportunities. Nowadays, IoT technologies have successfully been exploited in several domains, providing both social and economic benefits. The realization of the full potential of the next generation of the Internet of Things still needs further research efforts concerning, for instance, the identification of new architectures, methodologies, and infrastructures dealing with distributed and decentralized IoT systems; the integration of IoT with cognitive and social capabilities; the enhancement of the sensing–analysis–control cycle; the integration of consciousness and awareness in IoT environments; and the design of new algorithms and techniques for managing IoT big data. This Special Issue is devoted to advancements in technologies, methodologies, and applications for IoT, together with emerging standards and research topics which would lead to realization of the future Internet of Things

Development of BIM-based Automated Methods for Building Management and Structural Safety Assessment

Despite the progress made in modern project management methods, there is still a lack of appropriate automated tools that support digital integration over the project life cycle. There is considerable demand for fully embracing the latest technological opportunities such as Building Information Modeling (BIM), Internet of Things (IoT), Structural Health Monitoring (SHM), and prefabrication to support that digital transformation in construction. The aim of this study is to develop a set of automated management solutions and related tools to address the issues highlighted above. The thesis is presented as a collection of manuscripts of five peer-reviewed journal articles authored based on the present research. The first development is of a BIM-based method for 3D model visualization of buildings and their non-structural elements and their corresponding seismic risk levels and locations. It supports automated assessment of seismic risk of these elements. The second focuses on the development of a novel data-driven SHM technique to monitor the structural behavior of individual building modules to detect possible damages during their transportation. It consists of two main components, a sensor-based data acquisition (DAQ) and storage module, and an automated data analysis module that uses unsupervised machine learning techniques to identify damages during transportation using onboard captured acceleration data. It can be used to ascertain the safety of delivered modules before their assembly on site. The third accounts for the development of an automated BIM-based framework to facilitate effective data management and representation of sensory components of the SHM tool used in buildings. It allows for visualization of damages in building components based on the interpretation of the captured sensor data. It is designed to facilitate effective visualization capabilities for a rapid and efficient structural condition assessment. The fourth development is designed to dynamically update the thermal comfort data in monitored buildings by integrating their BIM models with captured sensor data. The default range utilized in this development is based on the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE) Standard. It is expected to provide a robust and practical tool for data collection, analysis, and visualization to facilitate intelligent monitoring of the thermal condition in buildings and help decision-makers take needed timely data-driven decisions. The fifth and last development is designed to alert IoT companies of malfunctioning of deployed sensors utilizing a BIM platform and a cloud database to process and transfer related actionable information

University of Southern California Heritage Hall- Fire Protection and Life Safety Analysis

This fire protection and life safety analysis is submitted in partial fulfillment of the requirements for the Master of Science Degree from California Polytechnic State University, San Luis Obispo. The study was performed on the University of Southern California’s Heritage Hall, which includes both a code-determined prescriptive examination and a performance-based analysis. The purpose of this review is to evaluate the Heritage Hall address based on compliance with all applicable codes and standards, as well as the determined occupant tenability criteria. The prescriptive examination of Heritage Hall consisted of the evaluation of all structural fire protection, egress analysis and design, water-based fire suppression, and fire alarm systems. This analysis was primarily performed by utilizing the 2013 edition of California Building Code and the 2013 editions of all applicable NFPA codes and standards. The structural fire protection overview provided an in-depth prescriptive analysis of the conversions made for Heritage Hall during the 2012 renovation project. The latest recapitalization expanded the lower level and added more spaces for student athletes, thus converting those locations to the A-3 occupancy classification. Per CBC Table 601, non-bearing walls and partitions were not required to be fire-rated. The structural update complied with all updated building codes due to a water curtain installed per Section 404.6 of the CBC, which allowed the center museum’s atrium not to be separated by a 1-hour fire barrier. Instead, both glass walls surrounding the atrium were used to create smoke partitions to meet standards. The egress analysis and design was utilized to determine new occupant loads for each floor, remove the B-2 occupancy classification, the creation of a new area of refuge. Per CBC Table 1018.1, corridor walls and ceilings were not required to be fire resistance rated due to the building being fully sprinklered. Only the area of refuge at the lower level was provided with a 1-hour fire rated separation, and existing 1-hour separations, such as the lower level’s exit access corridor, remained intact. Using the Life Safety Code, a building evacuation analysis was performed at Heritage Hall’s lower level. The average evacuation time of all lower level occupants was determined to be 5.43 minutes, with a range of 2.74-8.13 minutes depending on whether occupants used the exit corridor or the stairways. All egress components and occupancy classification were deemed acceptable. The water-based suppression analysis was performed by primarily using NFPA 13 and NFPA 25 codes and standards. A complete analysis of the building’s risers, sprinklers, and system demand calculations provided acceptable criteria for the water-based fire protection system installed. The outside overhang was chosen not to have sprinklers installed due to the large amount of remaining asbestos at the interstitial level near the ceiling. The overhang is made of concrete and directly exposed to the outside. The building’s fire alarm system was installed in 2012, with all new fire detection devices, notification appliances, fire alarm control panel, and a mass notification system. The fire alarm system design was analyzed using NFPA 72, with all spacing and location requirements deemed acceptable for the devices installed. All spot-type smoke and heat detectors are ceiling-mounted in accordance with the open ceiling plan at the lower level, which contains both ceiling and wall-mounted sprinklers. The performance-based analysis was performed using Fire Dynamics Simulator (FDS), a fire modeling program provided by NIST, and the SFPE Handbook of Fire Protection Engineering. Two unique design fire performance scenarios were established for Heritage Hall: a workstation fire in the first floor atrium and a stacked-chairs fire near the lower level exit corridor that prevents its use. In order to establish a basis for analysis and comparison, various tenability criteria were determined for the building’s occupants. The performance criteria consisted of visibility, toxicity, and tenability requirements for the facility, which were compared with modeling simulations created using FDS. The simulations allowed for the determination of the available safe egress time (ASET). Occupant behavior and characteristics were paired with Thunderhead Engineering’s Pathfinder program to provide a required set egress time (RSET) for each fire scenario. While the lower level corridor fire scenario met all tenability requirements, the atrium’s fire scenario simulation did not provide an acceptable ASET, and therefore did not pass the critical occupant visibility requirements for safe evacuation. Recommendations were provided to establish a legitimate smoke barrier per CBC Section 404.6, or an appropriate door separation for each side entrance to the atrium per CBC Section 715.1

Adopting Modern Fitness Sensors to Improve Patient Care

Technology found in modern fitness sensor devices advances at a very fast pace and current smartwatches are on the verge of closing the gap between being an everyday object and a medically reliable monitoring device. In this thesis, the possibility of adopting fitness sensor devices in medical environments is explored and use cases in which sensor devices can be deployed are examined. Their successful transfer from the area of sports to medical analyses and treatments may help patients to deal with their illnesses and to improve the level of patient care found today. Privacy and security issues as well as social concerns associated with such a disruptive evolution are discussed and practical tests of a pulse oximeter in various activities of daily living are conducted. The collected health data depicts a close representation of the performed activities. Furthermore, three types of fitness sensor devices were used in different real-life scenarios and the resulting data is compared. The results show that the recorded vital signs may differ significantly, depending on the scenario. ii

Studies on Sensor Aided Positioning and Context Awareness

This thesis studies Global Navigation Satellite Systems (GNSS) in combination with sensor systems that can be used for positioning and obtaining richer context information. When a GNSS is integrated with sensors, such as accelerometers, gyroscopes and barometric altimeters, valuable information can be produced for several applications; for example availability or/and performance of the navigation system can be increased. In addition to position technologies, GNSS devices are integrated more often with different types of technologies to fulfil several needs, e.g., different types of context recognition. The most common integrated devices are accelerometer, gyroscope, and magnetometer but also other sensors could be used.More specifically, this thesis presents sensor aided positioning with two satellite signals with altitude assistance. The method uses both pseudorange and Doppler measurements. The system is required to be stationary during the process and a source of altitude information, e.g., a MEMS barometer, is needed in addition to a basic GNSS receiver. Authentic pseudorange and Doppler measurements with simulated altitude were used used to test the algorithm. Results showed that normally the accuracy of couple of kilometers is acquired. Thesis also studies on what kind of errors barometric altimeter might encounter especially in personal positioning. The results show that barometers in differential mode provide highly accurate altitude solution (within tens of centimeters), but local disturbances in pressure need to be acknowledged in the application design. For example, heating, ventilating, and air conditioning in a car can have effect of few meters. Thus this could cause problems if the barometer is used as a altimeter for under meter-level positioning or navigation.We also explore methods for sensor aided GNSS systems for context recognition. First, the activity and environment recognition from mobile phone sensor and radio receiver data is investigated. The aim is in activity (e.g., walking, running, or driving a vehicle) and environment (e.g., street, home, or restaurant) detection. The thesis introduces an algorithm for user specific adaptation of the context model parameters using the feedback from the user, which can provide a confidence measure about the correctness of a classification. A real-life data collection campaign validate the proposed method. In addition, the thesis presents a concept for automated crash detection to motorcycles. In this concept, three different inertial measurement units are attached to the motorist’s helmet, torso of the motorist, and to the rear of the motor cycle. A maximum a posteriori classifier is trained to classify the crash and normal driving. Crash dummy tests were done by throwing the dummy from different altitudes to simulate the effect of crash to the motorist and real data is collected by driving the motorcycle. Preliminary results proved the potential of the proposed method could be applicable in real situations. In all the proposed systems in this thesis, knowledge of the context can help the positioning system, but also positioning system can help in determining the context