scholarly journals Developing a fuzzy logic based system for monitoring and early detection of residential fire based on thermistor sensors

2015 ◽  
Vol 12 (1) ◽  
pp. 63-89 ◽  
Author(s):  
Mirjana Maksimovic ◽  
Vladimir Vujovic ◽  
Branko Perisic ◽  
Vladimir Milosevic
Keyword(s):  
Fuzzy Logic ◽  
Real World ◽  
Network Performance ◽  
Performance Monitoring ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Critical Event ◽  
The Internet ◽  
Network Performance Monitoring

The recent proliferation of global networking has an enormous impact on the cooperation of smart elements, of arbitrary kind and purpose that can be located anywhere and interact with each other according to the predefined protocol. Furthermore, these elements have to be intelligently orchestrated in order to support distributed sensing and/or monitoring/control of real world phenomena. That is why the Internet of Things (IoT) concept raises like a new, promising paradigm for Future Internet development. Considering that Wireless Sensor Networks (WSNs) are envisioned as integral part of arbitrary IoTs, and the potentially huge number of cooperating IoTs that are usually used in the real world phenomena monitoring and management, the reliability of individual sensor nodes and the overall network performance monitoring and improvement are definitely challenging issues. One of the most interesting real world phenomena that can be monitored by WSN is indoor or outdoor fire. The incorporation of soft computing technologies, like fuzzy logic, in sensor nodes has to be investigated in order to gain the manageable network performance monitoring/control and the maximal extension of components life cycle. Many aspects, such as routes, channel access, locating, energy efficiency, coverage, network capacity, data aggregation and Quality of Services (QoS) have been explored extensively. In this article two fuzzy logic approaches, with temporal characteristics, are proposed for monitoring and determining confidence of fire in order to optimize and reduce the number of rules that have to be checked to make the correct decisions. We assume that this reduction may lower sensor activities without relevant impact on quality of operation and extend battery life directly contributing the efficiency, robustness and cost effectiveness of sensing network. In order to get a real time verification of proposed approaches a prototype sensor web node, based on Representational State Transfer (RESTful) services, is created as an infrastructure that supports fast critical event signaling and remote access to sensor data via the Internet.

scholarly journals Curriculum Learning for Natural Answer Generation

2018 ◽  
Author(s):  
Cao Liu ◽  
Shizhu He ◽  
Kang Liu ◽  
Jun Zhao
Keyword(s):  
Full Advantage ◽  
Real World ◽  
Large Scale ◽  
Question Answering ◽  
Generative Models ◽  
The Internet ◽  
Basic Model ◽  
The Arts ◽  
Learning Data

By reason of being able to obtain natural language responses, natural answers are more favored in real-world Question Answering (QA) systems. Generative models learn to automatically generate natural answers from large-scale question answer pairs (QA-pairs). However, they are suffering from the uncontrollable and uneven quality of QA-pairs crawled from the Internet. To address this problem, we propose a curriculum learning based framework for natural answer generation (CL-NAG), which is able to take full advantage of the valuable learning data from a noisy and uneven-quality corpus. Specifically, we employ two practical measures to automatically measure the quality (complexity) of QA-pairs. Based on the measurements, CL-NAG firstly utilizes simple and low-quality QA-pairs to learn a basic model, and then gradually learns to produce better answers with richer contents and more complete syntaxes based on more complex and higher-quality QA-pairs. In this way, all valuable information in the noisy and uneven-quality corpus could be fully exploited. Experiments demonstrate that CL-NAG outperforms the state-of-the-arts, which increases 6.8% and 8.7% in the accuracy for simple and complex questions, respectively.

Network Performance Monitoring, Fault Detection, Recovery, and Restoration

Grid Networks ◽  
2006 ◽  
pp. 253-275
Author(s):  
Richard Hughes-Jones ◽  
Yufeng Xin ◽  
Gigi Karmous-Edwards ◽  
John Strand
Keyword(s):  
Fault Detection ◽  
Network Performance ◽  
Performance Monitoring ◽  
Network Performance Monitoring

The Event Search Engine

2012 ◽  
pp. 70-82
Author(s):  
Takeshi Okadome ◽  
Yasue Kishino ◽  
Takuya Maekawa ◽  
Koji Kamei ◽  
Yutaka Yanagisawa ◽  
...  
Keyword(s):  
Search Engine ◽  
Real World ◽  
Local Environment ◽  
Real Space ◽  
Sensor Data ◽  
The Internet ◽  
Web Browser ◽  
Quantity Representation ◽  
Data Segment ◽  
The Web

In a remote or local environment in which a sensor network always collects data produced by sensors attached to physical objects, the engine presented here saves the data sent through the Internet and searches for data segments that correspond to real-world events by using natural language (NL) words in a query that are input in an web browser. The engine translates each query into a physical quantity representation searches for a sensor data segment that satisfies the representation, and sends back the event occurrence time, place, or related objects as a reply to the query to the remote or local environment in which the web browser displays them. The engine, which we expect to be one of the upcoming Internet services, exemplifies the concept of symbiosis that bridges the gaps between the real space and the digital space.

Traffic and Network Performance Monitoring for Effective Quality of Service and Network Management

2010 ◽  
pp. 201-227
Author(s):  
P. Papantoni-Kazakos ◽  
A. T. Burrell
Keyword(s):  
Mobile Networks ◽  
Network Performance ◽  
Performance Monitoring ◽  
Sequential Algorithm ◽  
Heterogeneous Environments ◽  
Time Varying ◽  
Distributed Environment ◽  
Data Flows ◽  
Network Performance Monitoring ◽  
And Performance

The authors consider distributed mobile networks carrying time-varying heterogeneous traffics. To deal effectively with the mobile and time-varying distributed environment, the deployment of traffic and network performance monitoring techniques is necessary for the identification of traffic changes, network failures, and also for the facilitation of protocol adaptations and topological modifications. Concurrently, the heterogeneous traffic environment necessitates the deployment of hybrid information transport techniques. This chapter discusses the design, analysis, and evaluation of distributed and dynamic techniques which manage the traffic and monitor the network performance effectively, while capturing the dynamics inherent in the mobile heterogeneous environments. Specifically, the design of a monitoring sub-network is sought, where the arising research tasks include: • the adoption of a core sequential algorithm which monitors both the variations in the rates of the information data flows and the dynamics of the network performance. • The identification of the specific operational and performance characteristics of the monitoring systems, when the core algorithm is implemented in a distributed environment; for a given network topology, it is important to identify the minimum size monitoring sub-network for complete “visibility” of data flows and network functions. • Dynamically changing monitoring sub-network architectures, as functions of time-varying network topologies. • The deployment of Artificial Intelligence learning techniques, in the presence of dynamically changing network and information flow environments, to appropriately adapt crucial operational parameters of the data monitoring algorithms.

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