INTRODUCTION TO WIRELESS SENSOR NETWORKS.
This powerpoint generally defines Wireless Sensor Networks, the advantages, disadvantages and the general types.
Presentation by Quaenet on what LoRaWAN is and the role it plays in the Internet of Things (IoT and IIoT). Presented at Silicon Halton IoT Peer2Peer group Sep 2018.
With the popularity of laptops, cell phones, PDAs, GPS devices, RFID, and intelligent electronics in the post-PC era, computing devices have become cheaper, more mobile, more distributed, and more pervasive in daily life. It is now possible to construct, from commercial off-the-shelf (COTS) components, a wallet size embedded system with the equivalent capability of a 90’s PC. Such embedded systems can be supported with scaled down Windows or Linux operating systems. From this perspective, the emergence of wireless sensor networks (WSNs) is essentially the latest trend of Moore’s Law toward the miniaturization and ubiquity of computing devices. Typically, a wireless sensor node (or simply sensor node) consists of sensing, computing, communication, actuation, and power components. These components are integrated on a single or multiple boards, and packaged in a few cubic inches. With state-of-the-art, low-power circuit and networking technologies, a sensor node powered by 2 AA batteries can last for up to three years with a 1% low duty cycle working mode. A WSN usually consists of tens to thousands of such nodes that communicate through wireless channels for information sharing and cooperative processing. WSNs can be deployed on a global scale for environmental monitoring and habitat study, over a battle field for military surveillance and reconnaissance, in emergent environments for search and rescue, in factories for condition based maintenance, in buildings for infrastructure health monitoring, in homes to realize smart homes, or even in bodies for patient monitoring [60; 76; 124; 142]. After the initial deployment (typically ad hoc), sensor nodes are responsible for self-organizing an appropriate network infrastructure, often with multi-hop connections between sensor nodes. The onboard sensors then start collecting acoustic, seismic, infrared or magnetic information about the environment, using either continuous or event driven working modes. Location and positioning information can also be obtained through the global positioning system (GPS) or local positioning algorithms. This information can be gathered from across the network and appropriately processed to construct a global view of the monitoring phenomena or objects. The basic philosophy behind WSNs is that, while the capability of each individual sensor node is limited, the aggregate power of the entire network is sufficient for the required mission. In a typical scenario, users can retrieve information of interest
from a WSN by injecting queries and gathering results from the so-called base stations (or sink nodes), which behave as an interface between users and the network. In this way, WSNs can be considered as a distributed database. It is also envisioned that sensor networks will ultimately be connected to the Internet, through which global information sharing becomes feasible. The era of WSNs is highly anticipated in the near future. In September 1999, WSNs w
Presentation by Quaenet on what LoRaWAN is and the role it plays in the Internet of Things (IoT and IIoT). Presented at Silicon Halton IoT Peer2Peer group Sep 2018.
With the popularity of laptops, cell phones, PDAs, GPS devices, RFID, and intelligent electronics in the post-PC era, computing devices have become cheaper, more mobile, more distributed, and more pervasive in daily life. It is now possible to construct, from commercial off-the-shelf (COTS) components, a wallet size embedded system with the equivalent capability of a 90’s PC. Such embedded systems can be supported with scaled down Windows or Linux operating systems. From this perspective, the emergence of wireless sensor networks (WSNs) is essentially the latest trend of Moore’s Law toward the miniaturization and ubiquity of computing devices. Typically, a wireless sensor node (or simply sensor node) consists of sensing, computing, communication, actuation, and power components. These components are integrated on a single or multiple boards, and packaged in a few cubic inches. With state-of-the-art, low-power circuit and networking technologies, a sensor node powered by 2 AA batteries can last for up to three years with a 1% low duty cycle working mode. A WSN usually consists of tens to thousands of such nodes that communicate through wireless channels for information sharing and cooperative processing. WSNs can be deployed on a global scale for environmental monitoring and habitat study, over a battle field for military surveillance and reconnaissance, in emergent environments for search and rescue, in factories for condition based maintenance, in buildings for infrastructure health monitoring, in homes to realize smart homes, or even in bodies for patient monitoring [60; 76; 124; 142]. After the initial deployment (typically ad hoc), sensor nodes are responsible for self-organizing an appropriate network infrastructure, often with multi-hop connections between sensor nodes. The onboard sensors then start collecting acoustic, seismic, infrared or magnetic information about the environment, using either continuous or event driven working modes. Location and positioning information can also be obtained through the global positioning system (GPS) or local positioning algorithms. This information can be gathered from across the network and appropriately processed to construct a global view of the monitoring phenomena or objects. The basic philosophy behind WSNs is that, while the capability of each individual sensor node is limited, the aggregate power of the entire network is sufficient for the required mission. In a typical scenario, users can retrieve information of interest
from a WSN by injecting queries and gathering results from the so-called base stations (or sink nodes), which behave as an interface between users and the network. In this way, WSNs can be considered as a distributed database. It is also envisioned that sensor networks will ultimately be connected to the Internet, through which global information sharing becomes feasible. The era of WSNs is highly anticipated in the near future. In September 1999, WSNs w
Wireless Sensor Networks UNIT-1
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The development of the wireless sensor networks (WSNs) in various applications like Defense, Health,
Environment monitoring, Industry etc. always attract many researchers in this field. WSN is the network
which consists of collection of tiny devices called sensor nodes. Sensor node typically combines wireless
radio transmitter-receiver and limited energy, restricted computational processing capacity and
communication band width. These sensor node sense some physical phenomenon using different
transduces. The current improvement in sensor technology has made possible WSNs that have wide and
varied applications. While selecting the right sensor for application a number of characteristics are
important. This paper provides the basics of WSNs including the node characteristics. It also throws light
on the different routing protocols.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
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CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
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Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
3. INTRODUCTION
• A Wireless Sensor Network(WSN)is a distributed network and it comprises a large number of
distributed, self-directed, tiny, low powered devices called sensor nodes
• WSN naturally encompasses a large number of spatially dispersed, petite, battery-operated,
embedded devices that are networked to supportively collect, process, and convey data to the
users, and it has restricted computing and processing capabilities.
• Now a days wireless network is the most popular services utilized in industrial and commercial
applications, because of its technical advancement in processor, communication, and usage of
low power embedded computing devices.
4. INTRO …….
• WSN is a wireless network that consists of base stations and numbers of nodes (wireless
sensors).
• A wireless sensor network is a group of specialized transducers with a communications
infrastructure for monitoring and recording conditions at diverse locations.
• Commonly monitored parameters are temperature, humidity, pressure, wind direction and
speed, illumination intensity, vibration intensity, sound intensity, power-line voltage,
chemical concentrations, pollutant levels and vital body functions.
5. INTRO…..
• Wireless sensor nodes are equipped with sensing unit, a processing unit,
communication unit and power unit. Each and every node is capable to perform
data gathering, sensing, processing and communicating with other nodes.The
sensing unit senses the environment, the processing unit computes the confined
permutations of the sensed data, and the communication unit performs exchange
of processed information among
• A sink or base station acts like an interface between users and the network. One
can retrieve required information from the network by injecting queries and
gathering results from the sink.
6. COMPONENTS OFWSNs
• Sensors are sophisticated devices that are frequently used to detect and respond
to electrical or optical signals.
• Transducers are devices that converts variations in a physical quantity, such as
pressure or brightness, into an electrical signal, or vice versa.
• Base stations are one or more components of the WSN with much more
computational, energy and communication resources. They act as a gateway
between sensor nodes and the end user as they typically forward data from the
WSN on to a server.
• A sensor node, also known as a mote (chiefly in North America), is a node in a
sensor network that is capable of performing some processing, gathering sensory
information and communicating with other connected nodes in the network.
8. EXAMPLES OF WSNTOPOLOGIES
StarTopologies
• Star topology is a communication topology, where each node connects directly to a
gateway. A single gateway can send or receive a message to a number of remote nodes.
In star topologies, the nodes are not permitted to send messages to each other. This
allows low-latency communications between the remote node and the gateway (base
station)
TreeTopologies
• Tree topology is also called as cascaded star topology. In tree topologies, each node
connects to a node that is placed higher in the tree, and then to the gateway. The main
advantage of the tree topology is that the expansion of a network can be easily
possible, and also error detection becomes easy. The disadvantage with this network is
that it relies heavily on the bus cable; if it breaks, all the network will collapse.
9. EXAMPLES OF WSNTOPOLOGIES
MeshTopologies
• The Mesh topologies allow transmission of data from one node to another,
which is within its radio transmission range. If a node wants to send a
message to another node, which is out of radio communication range, it
needs an intermediate node to forward the message to the desired node.
The advantage with this mesh topology includes easy isolation and
detection of faults in the network. The disadvantage is that the network is
large and requires huge investment.
10. Limitations ofWireless Sensor Networks
• Possess very little storage capacity – a few hundred kilobytes
• Possess modest processing power-8MHz
• Works in short communication range – consumes a lot of power
• Requires minimal energy – constrains protocols
• Have batteries with a finite life time
• Passive devices provide little energy
12. APPLICATIONS
• Potential applications of sensor networks include:
• Industrial automation
• Automated and smart homes
• Video surveillance
• Traffic monitoring
• Medical device monitoring
• Monitoring of weather conditions
• Air traffic control
• Robot control.
13. APPLICATIONS
• Military applications:Wireless sensor networks be likely an integral part of military
command, control, communications, computing, intelligence, battlefield
surveillance, reconnaissance and targeting systems.
• Area monitoring: In area monitoring, the sensor nodes are deployed over a region
where some phenomenon is to be monitored.When the sensors detect the event
being monitored (heat, pressure etc), the event is reported to one of the base
stations, which then takes appropriate action.
• Transportation: Real-time traffic information is being collected byWSNs to later
feed transportation models and alert drivers of congestion and traffic problems.
14. APPLICATIONS
• Health applications: Some of the health applications for sensor networks are
supporting interfaces for the disabled, integrated patient monitoring,
diagnostics, and drug administration in hospitals, tele-monitoring of human
physiological data, and tracking & monitoring doctors or patients inside a
hospital.
• Environmental sensing:The term Environmental Sensor Networks has
developed to cover many applications ofWSNs to earth science research.
This includes sensing volcanoes, oceans, glaciers, forests etc