11,243 research outputs found
Cloud Enabled Emergency Navigation Using Faster-than-real-time Simulation
State-of-the-art emergency navigation approaches are designed to evacuate
civilians during a disaster based on real-time decisions using a pre-defined
algorithm and live sensory data. Hence, casualties caused by the poor decisions
and guidance are only apparent at the end of the evacuation process and cannot
then be remedied. Previous research shows that the performance of routing
algorithms for evacuation purposes are sensitive to the initial distribution of
evacuees, the occupancy levels, the type of disaster and its as well its
locations. Thus an algorithm that performs well in one scenario may achieve bad
results in another scenario. This problem is especially serious in
heuristic-based routing algorithms for evacuees where results are affected by
the choice of certain parameters. Therefore, this paper proposes a
simulation-based evacuee routing algorithm that optimises evacuation by making
use of the high computational power of cloud servers. Rather than guiding
evacuees with a predetermined routing algorithm, a robust Cognitive Packet
Network based algorithm is first evaluated via a cloud-based simulator in a
faster-than-real-time manner, and any "simulated casualties" are then re-routed
using a variant of Dijkstra's algorithm to obtain new safe paths for them to
exits. This approach can be iterated as long as corrective action is still
possible.Comment: Submitted to PerNEM'15 for revie
A Cooperative Emergency Navigation Framework using Mobile Cloud Computing
The use of wireless sensor networks (WSNs) for emergency navigation systems
suffer disadvantages such as limited computing capacity, restricted battery
power and high likelihood of malfunction due to the harsh physical environment.
By making use of the powerful sensing ability of smart phones, this paper
presents a cloud-enabled emergency navigation framework to guide evacuees in a
coordinated manner and improve the reliability and resilience in both
communication and localization. By using social potential fields (SPF),
evacuees form clusters during an evacuation process and are directed to
egresses with the aid of a Cognitive Packet Networks (CPN) based algorithm.
Rather than just rely on the conventional telecommunications infrastructures,
we suggest an Ad hoc Cognitive Packet Network (AHCPN) based protocol to prolong
the life time of smart phones, that adaptively searches optimal communication
routes between portable devices and the egress node that provides access to a
cloud server with respect to the remaining battery power of smart phones and
the time latency.Comment: This document contains 8 pages and 3 figures and has been accepted by
ISCIS 2014 (29th International Symposium on Computer and Information
Sciences
Smart Signs: Showing the way in Smart Surroundings
This paper presents a context-aware guidance and messaging
system for large buildings and surrounding venues. Smart Signs are
a new type of electronic door- and way-sign based on wireless sensor networks.
Smart Signs present in-situ personalized guidance and messages,
are ubiquitous, and easy to understand. They combine the easiness of
use of traditional static signs with the flexibility and reactiveness of navigation
systems. The Smart Signs system uses context information such
as user’s mobility limitations, the weather, and possible emergency situations
to improve guidance and messaging.
Minimal infrastructure requirements and a simple deployment tool make
it feasible to easily deploy a Smart Signs system on demand.
An important design issue of the Smart Signs system is privacy: the
system secures communication links, does not track users, allow almost
complete anonymous use, and prevent the system to be used as a tool
for spying on users
WSN and RFID integration to support intelligent monitoring in smart buildings using hybrid intelligent decision support systems
The real time monitoring of environment context aware activities is becoming a standard in the service delivery in a wide range of domains (child and elderly care and supervision, logistics, circulation, and other). The safety of people, goods and premises depends on the prompt reaction to potential hazards identified at an early stage to engage appropriate control actions. This requires capturing real time data to process locally at the device level or communicate to backend systems for real time decision making. This research examines the wireless sensor network and radio frequency identification technology integration in smart homes to support advanced safety systems deployed upstream to safety and emergency response. These systems are based on the use of hybrid intelligent decision support systems configured in a multi-distributed architecture enabled by the wireless communication of detection and tracking data to support intelligent real-time monitoring in smart buildings. This paper introduces first the concept of wireless sensor network and radio frequency identification technology integration showing the various options for the task distribution between radio frequency identification and hybrid intelligent decision support systems. This integration is then illustrated in a multi-distributed system architecture to identify motion and control access in a smart building using a room capacity model for occupancy and evacuation, access rights and a navigation map automatically generated by the system. The solution shown in the case study is based on a virtual layout of the smart building which is implemented using the capabilities of the building information model and hybrid intelligent decision support system.The Saudi High Education Ministry and Brunel University (UK
Routing Diverse Evacuees with Cognitive Packets
This paper explores the idea of smart building evacuation when evacuees can
belong to different categories with respect to their ability to move and their
health conditions. This leads to new algorithms that use the Cognitive Packet
Network concept to tailor different quality of service needs to different
evacuees. These ideas are implemented in a simulated environment and evaluated
with regard to their effectiveness.Comment: 7 pages, 7 figure
An Indoor Navigation System Using a Sensor Fusion Scheme on Android Platform
With the development of wireless communication networks, smart phones have become a necessity for people’s daily lives, and they meet not only the needs of basic functions for users such as sending a message or making a phone call, but also the users’ demands for entertainment, surfing the Internet and socializing. Navigation functions have been commonly utilized, however the navigation function is often based on GPS (Global Positioning System) in outdoor environments, whereas a number of applications need to navigate indoors. This paper presents a system to achieve high accurate indoor navigation based on Android platform. To do this, we design a sensor fusion scheme for our system. We divide the system into three main modules: distance measurement module, orientation detection module and position update module. We use an efficient way to estimate the stride length and use step sensor to count steps in distance measurement module. For orientation detection module, in order to get the optimal result of orientation, we then introduce Kalman filter to de-noise the data collected from different sensors. In the last module, we combine the data from the previous modules and calculate the current location. Results of experiments show that our system works well and has high accuracy in indoor situations
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