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

Digital seismo-acoustic signal processing aboard a wireless sensor array for volcano monitoring

This work describes the design and implementation of a low cost wireless sensor array utilizing digital processing to conduct autonomous real-time seismo-acoustic signal analysis of earthquakes at actively erupting volcanoes. The array consists of (1) three sensor nodes, which comprise seismic and acoustic sensors, (2) a GPS-based time synchronization node, and (3) a base receiver node, which features a communication channel for long distance telemetry. These nodes are based on the Moteiv TMote Sky wireless platform. The signal analysis accomplishes Real-time Seismic-Amplitude Measurement (RSAM) and Seismic Spectral-Amplitude Measurement (SSAM) calculations, and the extraction of triggered arrival time, event duration, intensity, and a decimated version of the triggered events for both channels. These elements are fundamental descriptors of earthquake activity. The processed data from the sensor nodes are transmitted back to the central node, where additional processing may be performed. This final information can be transmitted periodically via low bandwidth telemetry options

Real-time In-situ Seismic Tomography in Sensor Network

Seismic tomography is a technique for illuminating the physical dynamics of the Earth by seismic waves generated by earthquakes or explosions. In both industry and academia, the seismic exploration does not yet have the capability of imaging seismic tomography in real-time and with high resolution. There are two reasons. First, at present raw seismic data are typically recorded on sensor nodes locally then are manually collected to central observatories for post processing, and this process may take months to complete. Second, high resolution tomography requires a large and dense sensor network, the real-time data retrieval from a network of large-amount wireless seismic nodes to a central server is virtually impossible due to the sheer data amount and resource limitations. This limits our ability to understand earthquake zone or volcano dynamics. To obtain the seismic tomography in real-time and high resolution, a new design of sensor network system for raw seismic data processing and distributed tomography computation is demanded. Based on these requirements, three research aspects are addressed in this work. First, a distributed multi-resolution evolving tomography computation algorithm is proposed to compute tomography in the network, while avoiding costly data collections and centralized computations. Second, InsightTomo, an end-to-end sensor network emulation platform, is designed to emulate the entire process from data recording to tomography image result delivery. Third, a sensor network testbed is presented to verify the related methods and design in real world. The design of the platform consists of hardware, sensing and data processing components

Direct monitoring of active geohazards: emerging geophysical tools for deep-water assessments

Seafloor networks of cables, pipelines, and other infrastructure underpin our daily lives, providing communication links, information, and energy supplies. Despite their global importance, these networks are vulnerable to damage by a number of natural seafloor hazards, including landslides, turbidity currents, fluid flow, and scour. Conventional geophysical techniques, such as high-resolution reflection seismic and side-scan sonar, are commonly employed in geohazard assessments. These conventional tools provide essential information for route planning and design; however, such surveys provide only indirect evidence of past processes and do not observe or measure the geohazard itself. As such, many numerical-based impact models lack field-scale calibration, and much uncertainty exists about the triggers, nature, and frequency of deep-water geohazards. Recent advances in technology now enable a step change in their understanding through direct monitoring. We outline some emerging monitoring tools and how they can quantify key parameters for deepwater geohazard assessment. Repeat seafloor surveys in dynamic areas show that solely relying on evidence from past deposits can lead to an under-representation of the geohazard events. Acoustic Doppler current profiling provides new insights into the structure of turbidity currents, whereas instrumented mobile sensors record the nature of movement at the base of those flows for the first time. Existing and bespoke cabled networks enable high bandwidth, low power, and distributed measurements of parameters such as strain across large areas of seafloor. These techniques provide valuable new measurements that will improve geohazard assessments and should be deployed in a complementary manner alongside conventional geophysical tools

Debris-flow monitoring and warning: review and examples

Debris flows represent one of the most dangerous types of mass movements, because of their high velocities, large impact forces and long runout distances. This review describes the available debris-flow monitoring techniques and proposes recommendations to inform the design of future monitoring and warning/alarm systems. The selection and application of these techniques is highly dependent on site and hazard characterization, which is illustrated through detailed descriptions of nine monitoring sites: five in Europe, three in Asia and one in the USA. Most of these monitored catchments cover less than ~10 km2 and are topographically rugged with Melton Indices greater than 0.5. Hourly rainfall intensities between 5 and 15 mm/h are sufficient to trigger debris flows at many of the sites, and observed debris-flow volumes range from a few hundred up to almost one million cubic meters. The sensors found in these monitoring systems can be separated into two classes: a class measuring the initiation mechanisms, and another class measuring the flow dynamics. The first class principally includes rain gauges, but also contains of soil moisture and pore-water pressure sensors. The second class involves a large variety of sensors focusing on flow stage or ground vibrations and commonly includes video cameras to validate and aid in the data interpretation. Given the sporadic nature of debris flows, an essential characteristic of the monitoring systems is the differentiation between a continuous mode that samples at low frequency (“non-event mode”) and another mode that records the measurements at high frequency (“event mode”). The event detection algorithm, used to switch into the “event mode” depends on a threshold that is typically based on rainfall or ground vibration. Identifying the correct definition of these thresholds is a fundamental task not only for monitoring purposes, but also for the implementation of warning and alarm systemsPeer ReviewedPostprint (author's final draft

Integrating Science Needs with Advanced Seafloor Sensor Engineering to Provide Early Warning of Geohazards: Visioning Workshop and Roadmap for the Future

The workshop was funded by the National Science Foundation (NSF), OCE Division of Ocean Sciences (Award # 1817257). This report summarizes the key findings, outcomes, and recommendations of the workshop and serves as a draft of the comprehensive roadmap

Aerial Seismology Using Balloon-Based Barometers

Seismology on Venus has long eluded planetary scientists due to extreme temperature and pressure conditions on its surface, which most electronics cannot withstand for mission durations required for ground-based seismic studies. We show that infrasonic (low-frequency) pressure fluctuations, generated as a result of ground motion, produced by an artificial seismic source known as a seismic hammer, and recorded using sensitive microbarometers deployed on a tethered balloon, are able to replicate the frequency content of ground motion. We also show that weak, artificial seismic activity thus produced may be geolocated by using multiple airborne barometers. The success of this technique paves the way for balloon-based aero-seismology, leading to a potentially revolutionary method to perform seismic studies from a remote airborne station on the earth and solar system objects with substantial atmospheres such as Venus and Titan