This document discusses wireless sensor networks (WSNs) and their applications. It describes WSNs as collections of inexpensive computational nodes that measure environmental conditions and forward data to a central point. It divides WSNs into two categories:
Category 1 WSNs (C1WSNs) consist of many nodes in a mesh network with multi-hop routing. They are used for applications like military monitoring that require large areas and distances between nodes.
Category 2 WSNs (C2WSNs) have star-based single-hop networks with static routing and shorter distances between nodes. They are used for applications like home automation with direct connections between nodes and a central hub.
The document provides examples of various
Sensor Networks Introduction and ArchitecturePeriyanayagiS
This document provides an overview of sensor networks and wireless sensor network architectures. It begins with an introduction to wireless sensor networks and their components. It then discusses the topics, challenges, and enabling technologies for WSNs. The document outlines the architecture of a sensor node and its goals. It provides examples of WSN applications and discusses sensor network deployment considerations. Finally, it addresses the design challenges, operational challenges, and required mechanisms for WSNs to meet their requirements.
Contiki is an open source operating system for the Internet of Things. Contiki connects tiny low-cost, low-power microcontrollers to the Internet.
the presentation explains how to install the simulator, teach the reader some concepts of contiki OS, goes through API used in platform specific examples, and most importantly explains some example(Blinking example, Light and temperature sensor web demo).
This document presents information about the MicaZ and TelosB sensor motes. It provides details on the hardware and software components of the MicaZ mote, including its microprocessor, radio, memory, inputs/outputs, and support for the TinyOS operating system and nesC programming language. Specifications of the TelosB mote are also given, noting its use of a different microcontroller than MicaZ. A comparison shows the MicaZ has higher power consumption while the TelosB has faster wakeup times and is not modular.
This document discusses wireless sensor networks and sensor node technology. It provides details on the basic components and functionality of wireless sensor nodes, including hardware components like sensors, processing units, and communication units. It also describes software subsystems like operating systems, sensor drivers, and data processing applications. The document outlines design constraints for wireless sensor networks and trends toward miniaturization and integration. It summarizes research efforts to develop new sensor technologies, arrayed sensor networks, and techniques for interpreting sensor data for decision-making.
This document discusses sources of IoT including popular IoT development boards, the role of RFID, and wireless sensor networks. RFID enables tracking and inventory control through identification. Wireless sensor networks allow sensors to monitor physical conditions from remote locations through wireless communication. Each wireless sensor node can perform computations and wireless networking to connect sensors autonomously in a wireless sensor network.
The document discusses wireless sensor networks and their applications. It describes wireless sensor networks as consisting of individual nodes that can interact with their environment by sensing or controlling physical parameters. It then discusses several applications of wireless sensor networks, including disaster relief, environment monitoring, intelligent buildings, facility management, machine maintenance, agriculture, healthcare, and logistics. Finally, it outlines some key requirements and mechanisms needed to implement wireless sensor networks, including communication, energy efficiency, self-configuration, collaboration, data-centric operation, and exploiting tradeoffs between different needs.
EC8702 adhoc and wireless sensor networks iv eceGOWTHAMMS6
This document outlines the syllabus for a course on Adhoc and Wireless Sensor Networks. It covers five units: (1) Introduction to Adhoc Networks and routing protocols, (2) Introduction to sensor networks and architectures, (3) Networking concepts and protocols for sensor networks, (4) Security issues in sensor networks, and (5) Sensor network platforms and tools. Some key topics discussed include characteristics of adhoc networks, challenges in routing, components and applications of wireless sensor networks, and medium access schemes. The objectives are for students to learn the fundamentals and apply their knowledge to identify suitable protocols based on network requirements and understand security and transport layer issues in these networks.
Routing protocols in wireless sensor networks face several unique challenges compared to other wireless networks. The document discusses these challenges and provides an overview of common routing protocol approaches in WSNs, including flat routing protocols like SPIN and Directed Diffusion, hierarchical routing protocols like LEACH, and location-based routing protocols. It also covers routing design issues specific to WSNs such as energy efficiency, data delivery models, fault tolerance, and quality of service.
Sensor Networks Introduction and ArchitecturePeriyanayagiS
This document provides an overview of sensor networks and wireless sensor network architectures. It begins with an introduction to wireless sensor networks and their components. It then discusses the topics, challenges, and enabling technologies for WSNs. The document outlines the architecture of a sensor node and its goals. It provides examples of WSN applications and discusses sensor network deployment considerations. Finally, it addresses the design challenges, operational challenges, and required mechanisms for WSNs to meet their requirements.
Contiki is an open source operating system for the Internet of Things. Contiki connects tiny low-cost, low-power microcontrollers to the Internet.
the presentation explains how to install the simulator, teach the reader some concepts of contiki OS, goes through API used in platform specific examples, and most importantly explains some example(Blinking example, Light and temperature sensor web demo).
This document presents information about the MicaZ and TelosB sensor motes. It provides details on the hardware and software components of the MicaZ mote, including its microprocessor, radio, memory, inputs/outputs, and support for the TinyOS operating system and nesC programming language. Specifications of the TelosB mote are also given, noting its use of a different microcontroller than MicaZ. A comparison shows the MicaZ has higher power consumption while the TelosB has faster wakeup times and is not modular.
This document discusses wireless sensor networks and sensor node technology. It provides details on the basic components and functionality of wireless sensor nodes, including hardware components like sensors, processing units, and communication units. It also describes software subsystems like operating systems, sensor drivers, and data processing applications. The document outlines design constraints for wireless sensor networks and trends toward miniaturization and integration. It summarizes research efforts to develop new sensor technologies, arrayed sensor networks, and techniques for interpreting sensor data for decision-making.
This document discusses sources of IoT including popular IoT development boards, the role of RFID, and wireless sensor networks. RFID enables tracking and inventory control through identification. Wireless sensor networks allow sensors to monitor physical conditions from remote locations through wireless communication. Each wireless sensor node can perform computations and wireless networking to connect sensors autonomously in a wireless sensor network.
The document discusses wireless sensor networks and their applications. It describes wireless sensor networks as consisting of individual nodes that can interact with their environment by sensing or controlling physical parameters. It then discusses several applications of wireless sensor networks, including disaster relief, environment monitoring, intelligent buildings, facility management, machine maintenance, agriculture, healthcare, and logistics. Finally, it outlines some key requirements and mechanisms needed to implement wireless sensor networks, including communication, energy efficiency, self-configuration, collaboration, data-centric operation, and exploiting tradeoffs between different needs.
EC8702 adhoc and wireless sensor networks iv eceGOWTHAMMS6
This document outlines the syllabus for a course on Adhoc and Wireless Sensor Networks. It covers five units: (1) Introduction to Adhoc Networks and routing protocols, (2) Introduction to sensor networks and architectures, (3) Networking concepts and protocols for sensor networks, (4) Security issues in sensor networks, and (5) Sensor network platforms and tools. Some key topics discussed include characteristics of adhoc networks, challenges in routing, components and applications of wireless sensor networks, and medium access schemes. The objectives are for students to learn the fundamentals and apply their knowledge to identify suitable protocols based on network requirements and understand security and transport layer issues in these networks.
Routing protocols in wireless sensor networks face several unique challenges compared to other wireless networks. The document discusses these challenges and provides an overview of common routing protocol approaches in WSNs, including flat routing protocols like SPIN and Directed Diffusion, hierarchical routing protocols like LEACH, and location-based routing protocols. It also covers routing design issues specific to WSNs such as energy efficiency, data delivery models, fault tolerance, and quality of service.
This document discusses localization techniques in wireless sensor networks (WSNs). It begins with an introduction to WSNs and their applications that require location information. While GPS could provide location data, it is not practical for WSNs due to cost and physical constraints. The document then categorizes localization methods as range-based, which use distance or angle measurements, and range-free, which do not directly measure distance. Specific techniques like time of arrival, received signal strength, and DV-Hop localization are described. The document concludes with classifications of localization methods and topics for future work.
This document discusses wireless sensor networks and middleware approaches for them. It describes wireless sensor networks as consisting of distributed autonomous sensor nodes that monitor physical environments cooperatively. It outlines common sensor node components and network architectures. It then defines middleware as a software layer that manages complexity and heterogeneity. Key middleware design principles for wireless sensor networks include supporting limited resources, scalability, and data aggregation. The document outlines several middleware approaches, including those based on global behavior, local behavior, virtual machines, databases, and modular programming.
This document provides an overview of wireless sensor networks. It discusses key definitions, advantages, applications and challenges. Sensor networks can provide energy and detection advantages over traditional systems. They enable applications in various domains including military, environmental monitoring, healthcare and home automation. The document also outlines enabling technologies and discusses important considerations like network architectures, hardware components, energy consumption and optimization goals.
This document provides an overview of wireless ad-hoc networks. It discusses the definition and types of multi-hop wireless networks. Some key technical challenges for ad-hoc networks are limited wireless range, mobility, and energy constraints. The document reviews several media access and routing protocols used in ad-hoc networks, including MACA, DSDV, AODV and DSR. It also discusses providing quality of service in ad-hoc networks and some of the challenges in routing, maintenance and variable resources. In conclusion, the document states that flexibility, low cost and applications make ad-hoc networks an essential part of future pervasive computing environments.
The document discusses routing challenges and protocols in wireless sensor networks (WSNs). It covers flooding, hierarchical routing protocols like LEACH, data-centric protocols like directed diffusion, and negotiation-based protocols like SPIN. It also discusses resource constraints in WSNs like limited energy and the need for routing protocols to be energy-efficient. Unique characteristics of WSNs like dynamic topology and varying node densities present new challenges for routing protocol design.
This document provides an overview of wireless sensor networks and their applications. It discusses that a sensor network is comprised of sensing, computing, and communication elements that allow an administrator to instrument, observe and react to events in an environment. There are typically four basic components: sensors, an interconnecting network, a central point for information clustering, and computing resources to handle the data. Common applications of sensor networks include military surveillance, environmental monitoring, and infrastructure/facility monitoring.
This document discusses wireless sensor networks and routing protocols. It covers several key topics:
1) It describes single-hop and multihop data transmission in wireless sensor networks and the advantages of multihop in increasing network lifetime and reducing interference.
2) It discusses routing challenges in wireless sensor networks due to constraints like energy, bandwidth and changing environments. It also covers routing strategies like proactive, reactive and hybrid routing.
3) It provides details on common routing protocols for wireless sensor networks like flooding, gossiping, SPIN and LEACH, outlining their key mechanisms and advantages/disadvantages. LEACH uses clustering to improve energy efficiency.
This document discusses wireless sensor network applications and energy consumption. It provides examples of WSN applications including disaster relief, environment monitoring, healthcare, and more. It then discusses various factors that influence energy consumption in sensor nodes, including operation states, microcontroller usage, radio transceivers, memory, and the relationship between computation and communication. Specific power consumption numbers are given for different components like radios, sensors, and microprocessors. The goals of optimization for WSNs are discussed as quality of service, energy efficiency, scalability, and robustness.
UNIT IV WIRELESS SENSOR NETWORKS (WSNS) AND MAC PROTOCOLS 9 Single node architecture: hardware and software components of a sensor node - WSN Network architecture: typical network architectures-data relaying and aggregation strategies -MAC layer protocols: self-organizing, Hybrid TDMA/FDMA and CSMA based MAC- IEEE 802.15.4.
How to put these nodes together to form a meaningful network.
How a network should function at high-level application scenarios .
On the basis of these scenarios and optimization goals, the design of networking protocols in wireless sensor networks are derived
A proper service interface is required and integration of WSNs into larger network contexts.
This document discusses network management for wireless sensor networks. It begins with an introduction to traditional network management models and then discusses key design issues for network management in WSNs including power efficiency, scalability, and simplicity. It provides MANNA as an example management architecture for WSNs and discusses other related issues like naming, localization, and fault tolerance. The document also outlines applications of WSNs such as habitat monitoring, structural monitoring, and smart roads.
This document provides an overview of routing protocols in ad hoc networks. It begins with an abstract describing the objectives of surveying and comparing different classes of ad hoc routing protocols. The document then outlines the topics to be covered, including the characteristics, applications, and types of ad hoc routing protocols. Several representative routing protocols are described in detail, including table-driven, hybrid, source-initiated, location-aware, multipath, hierarchical, multicast, and power-aware protocols. The document concludes by discussing future work related to improving reusability and security of ad hoc routing protocols.
The document discusses ad hoc networks and wireless sensor networks. It defines an ad hoc network as a temporary network composed of mobile nodes without preexisting infrastructure that is self-organizing. Wireless sensor networks are introduced as a collection of sensor nodes densely deployed to monitor conditions and cooperatively pass data back to central nodes. The document outlines key characteristics of both networks including their temporary and adaptive nature, multi-hop routing, and challenges of mobility, power constraints, and dynamic topology changes.
Minimize energy per packet (or per bit)
Maximize network lifetime
Routing considering available battery energy
Maximum Total Available Battery Capacity
Minimum Battery Cost Routing (MBCR)
Min– Max Battery Cost Routing (MMBCR)
Conditional Max – Min Battery Capacity Routing (CMMBCR)
Minimize variance in power levels
Minimum Total Transmission Power Routing (MTPR)
TinyOS is an open source operating system designed for wireless sensor networks. It uses a component-based architecture and event-driven execution model to achieve low power consumption and memory footprint. TinyOS programs are built by wiring together components that provide and use interfaces to communicate through events and commands. It also uses a non-preemptive task scheduler and static memory allocation to improve efficiency for energy constrained sensor nodes. The nesC language extends C to support TinyOS's programming model and execution model.
This document discusses geographical routing in mobile ad hoc networks. It describes traditional routing approaches like next-hop routing, source routing, and flooding, and their disadvantages. It then introduces geographical routing, which uses location information to route packets. Key geographical routing protocols discussed include LAR, DREAM, and GRID. LAR and DREAM disseminate location information and forward packets towards the destination's expected zone. GRID partitions the area into grids and elects gateways to route between grids towards the destination. The document also categorizes geographical routing algorithms based on their use of location services, forwarding strategies, and recovery schemes.
This document discusses power aware routing protocols for wireless sensor networks. It begins by describing wireless sensor networks and how they are used to monitor environmental conditions. It then classifies routing protocols for sensor networks based on their functioning, node participation style, and network structure. Specific examples are provided for different types of routing protocols, including LEACH, TEEN, APTEEN, SPIN, Rumor Routing, and PEGASIS. Chain-based and clustering routing protocols are also summarized.
The document discusses several challenges in embedded systems design. It notes that current scientific foundations separate hardware and software design paradigms in ways that make integrating computation and physical constraints difficult. Engineering practices also separate critical and best-effort design methods. The document argues that a successful approach to embedded systems design needs a mathematical basis that integrates abstract-machine and transfer-function models, allows combining critical and best-effort engineering, and encompasses heterogeneous components through constructs like compositionality and non-interference rules.
Physical channels carry information over the air interface between the mobile station and base transceiver station. Logical channels map user data and signaling information onto physical channels. There are two main types of logical channels - traffic channels which carry call data, and control channels which communicate service information. Control channels include broadcast channels which transmit cell-wide information, common channels used for paging and access procedures, and dedicated channels for signaling during calls or when not on a call. Logical channels are mapped onto physical channels to effectively transmit information wirelessly between network components in a GSM system.
This document provides an overview of wireless sensor networks. It discusses wireless communication technologies, the need for wireless communication, and defines wireless sensor networks. It describes the characteristics, architecture, operating systems, applications, and technical challenges of wireless sensor networks. Finally, it discusses some companies that manufacture wireless sensor network products, including Cisco, IBM, and Libelium.
Wireless sensor networks consist of distributed autonomous sensors that monitor physical or environmental conditions. Sensor nodes gather data and transmit it to a central location. Wireless sensor networks have applications in fields like military surveillance, environmental monitoring, healthcare, home automation, and traffic control. The design of wireless sensor networks is influenced by factors like fault tolerance, scalability, hardware constraints, topology, and power consumption.
This document discusses localization techniques in wireless sensor networks (WSNs). It begins with an introduction to WSNs and their applications that require location information. While GPS could provide location data, it is not practical for WSNs due to cost and physical constraints. The document then categorizes localization methods as range-based, which use distance or angle measurements, and range-free, which do not directly measure distance. Specific techniques like time of arrival, received signal strength, and DV-Hop localization are described. The document concludes with classifications of localization methods and topics for future work.
This document discusses wireless sensor networks and middleware approaches for them. It describes wireless sensor networks as consisting of distributed autonomous sensor nodes that monitor physical environments cooperatively. It outlines common sensor node components and network architectures. It then defines middleware as a software layer that manages complexity and heterogeneity. Key middleware design principles for wireless sensor networks include supporting limited resources, scalability, and data aggregation. The document outlines several middleware approaches, including those based on global behavior, local behavior, virtual machines, databases, and modular programming.
This document provides an overview of wireless sensor networks. It discusses key definitions, advantages, applications and challenges. Sensor networks can provide energy and detection advantages over traditional systems. They enable applications in various domains including military, environmental monitoring, healthcare and home automation. The document also outlines enabling technologies and discusses important considerations like network architectures, hardware components, energy consumption and optimization goals.
This document provides an overview of wireless ad-hoc networks. It discusses the definition and types of multi-hop wireless networks. Some key technical challenges for ad-hoc networks are limited wireless range, mobility, and energy constraints. The document reviews several media access and routing protocols used in ad-hoc networks, including MACA, DSDV, AODV and DSR. It also discusses providing quality of service in ad-hoc networks and some of the challenges in routing, maintenance and variable resources. In conclusion, the document states that flexibility, low cost and applications make ad-hoc networks an essential part of future pervasive computing environments.
The document discusses routing challenges and protocols in wireless sensor networks (WSNs). It covers flooding, hierarchical routing protocols like LEACH, data-centric protocols like directed diffusion, and negotiation-based protocols like SPIN. It also discusses resource constraints in WSNs like limited energy and the need for routing protocols to be energy-efficient. Unique characteristics of WSNs like dynamic topology and varying node densities present new challenges for routing protocol design.
This document provides an overview of wireless sensor networks and their applications. It discusses that a sensor network is comprised of sensing, computing, and communication elements that allow an administrator to instrument, observe and react to events in an environment. There are typically four basic components: sensors, an interconnecting network, a central point for information clustering, and computing resources to handle the data. Common applications of sensor networks include military surveillance, environmental monitoring, and infrastructure/facility monitoring.
This document discusses wireless sensor networks and routing protocols. It covers several key topics:
1) It describes single-hop and multihop data transmission in wireless sensor networks and the advantages of multihop in increasing network lifetime and reducing interference.
2) It discusses routing challenges in wireless sensor networks due to constraints like energy, bandwidth and changing environments. It also covers routing strategies like proactive, reactive and hybrid routing.
3) It provides details on common routing protocols for wireless sensor networks like flooding, gossiping, SPIN and LEACH, outlining their key mechanisms and advantages/disadvantages. LEACH uses clustering to improve energy efficiency.
This document discusses wireless sensor network applications and energy consumption. It provides examples of WSN applications including disaster relief, environment monitoring, healthcare, and more. It then discusses various factors that influence energy consumption in sensor nodes, including operation states, microcontroller usage, radio transceivers, memory, and the relationship between computation and communication. Specific power consumption numbers are given for different components like radios, sensors, and microprocessors. The goals of optimization for WSNs are discussed as quality of service, energy efficiency, scalability, and robustness.
UNIT IV WIRELESS SENSOR NETWORKS (WSNS) AND MAC PROTOCOLS 9 Single node architecture: hardware and software components of a sensor node - WSN Network architecture: typical network architectures-data relaying and aggregation strategies -MAC layer protocols: self-organizing, Hybrid TDMA/FDMA and CSMA based MAC- IEEE 802.15.4.
How to put these nodes together to form a meaningful network.
How a network should function at high-level application scenarios .
On the basis of these scenarios and optimization goals, the design of networking protocols in wireless sensor networks are derived
A proper service interface is required and integration of WSNs into larger network contexts.
This document discusses network management for wireless sensor networks. It begins with an introduction to traditional network management models and then discusses key design issues for network management in WSNs including power efficiency, scalability, and simplicity. It provides MANNA as an example management architecture for WSNs and discusses other related issues like naming, localization, and fault tolerance. The document also outlines applications of WSNs such as habitat monitoring, structural monitoring, and smart roads.
This document provides an overview of routing protocols in ad hoc networks. It begins with an abstract describing the objectives of surveying and comparing different classes of ad hoc routing protocols. The document then outlines the topics to be covered, including the characteristics, applications, and types of ad hoc routing protocols. Several representative routing protocols are described in detail, including table-driven, hybrid, source-initiated, location-aware, multipath, hierarchical, multicast, and power-aware protocols. The document concludes by discussing future work related to improving reusability and security of ad hoc routing protocols.
The document discusses ad hoc networks and wireless sensor networks. It defines an ad hoc network as a temporary network composed of mobile nodes without preexisting infrastructure that is self-organizing. Wireless sensor networks are introduced as a collection of sensor nodes densely deployed to monitor conditions and cooperatively pass data back to central nodes. The document outlines key characteristics of both networks including their temporary and adaptive nature, multi-hop routing, and challenges of mobility, power constraints, and dynamic topology changes.
Minimize energy per packet (or per bit)
Maximize network lifetime
Routing considering available battery energy
Maximum Total Available Battery Capacity
Minimum Battery Cost Routing (MBCR)
Min– Max Battery Cost Routing (MMBCR)
Conditional Max – Min Battery Capacity Routing (CMMBCR)
Minimize variance in power levels
Minimum Total Transmission Power Routing (MTPR)
TinyOS is an open source operating system designed for wireless sensor networks. It uses a component-based architecture and event-driven execution model to achieve low power consumption and memory footprint. TinyOS programs are built by wiring together components that provide and use interfaces to communicate through events and commands. It also uses a non-preemptive task scheduler and static memory allocation to improve efficiency for energy constrained sensor nodes. The nesC language extends C to support TinyOS's programming model and execution model.
This document discusses geographical routing in mobile ad hoc networks. It describes traditional routing approaches like next-hop routing, source routing, and flooding, and their disadvantages. It then introduces geographical routing, which uses location information to route packets. Key geographical routing protocols discussed include LAR, DREAM, and GRID. LAR and DREAM disseminate location information and forward packets towards the destination's expected zone. GRID partitions the area into grids and elects gateways to route between grids towards the destination. The document also categorizes geographical routing algorithms based on their use of location services, forwarding strategies, and recovery schemes.
This document discusses power aware routing protocols for wireless sensor networks. It begins by describing wireless sensor networks and how they are used to monitor environmental conditions. It then classifies routing protocols for sensor networks based on their functioning, node participation style, and network structure. Specific examples are provided for different types of routing protocols, including LEACH, TEEN, APTEEN, SPIN, Rumor Routing, and PEGASIS. Chain-based and clustering routing protocols are also summarized.
The document discusses several challenges in embedded systems design. It notes that current scientific foundations separate hardware and software design paradigms in ways that make integrating computation and physical constraints difficult. Engineering practices also separate critical and best-effort design methods. The document argues that a successful approach to embedded systems design needs a mathematical basis that integrates abstract-machine and transfer-function models, allows combining critical and best-effort engineering, and encompasses heterogeneous components through constructs like compositionality and non-interference rules.
Physical channels carry information over the air interface between the mobile station and base transceiver station. Logical channels map user data and signaling information onto physical channels. There are two main types of logical channels - traffic channels which carry call data, and control channels which communicate service information. Control channels include broadcast channels which transmit cell-wide information, common channels used for paging and access procedures, and dedicated channels for signaling during calls or when not on a call. Logical channels are mapped onto physical channels to effectively transmit information wirelessly between network components in a GSM system.
This document provides an overview of wireless sensor networks. It discusses wireless communication technologies, the need for wireless communication, and defines wireless sensor networks. It describes the characteristics, architecture, operating systems, applications, and technical challenges of wireless sensor networks. Finally, it discusses some companies that manufacture wireless sensor network products, including Cisco, IBM, and Libelium.
Wireless sensor networks consist of distributed autonomous sensors that monitor physical or environmental conditions. Sensor nodes gather data and transmit it to a central location. Wireless sensor networks have applications in fields like military surveillance, environmental monitoring, healthcare, home automation, and traffic control. The design of wireless sensor networks is influenced by factors like fault tolerance, scalability, hardware constraints, topology, and power consumption.
Wireless sensor network and its applicationRoma Vyas
The document discusses wireless sensor networks (WSN) and their applications. It defines a WSN as a collection of sensor nodes that communicate wirelessly and self-organize after deployment. Sensor nodes collect data at regular intervals, convert it to electrical signals, and send it to a base station. The document outlines the components of sensor nodes and describes how WSNs are used for applications like forest fire detection, air/water pollution monitoring, landslide detection, and military surveillance. It also discusses the TinyOS operating system commonly used for WSNs and its features for efficiently utilizing energy in sensor nodes.
Wireless Sensor Networks are networks that consists of sensors which are distributed in an ad hoc manner.
These sensors work with each other to sense some physical phenomenon and then the information gathered is processed to get relevant results.Wireless sensor networks consists of protocols and algorithms with self-organizing capabilities
This document provides an overview of wireless sensor networks (WSNs). It describes the architecture of WSNs including sensor nodes, transceivers and controllers. It discusses different types of WSNs such as terrestrial, underground, underwater, multimedia and mobile WSNs. It also covers WSN topologies, characteristics, applications and limitations. The key aspects of WSNs are that they are made up of spatially distributed sensors to monitor environmental conditions and wireless connectivity is used to transmit sensor data to a central location for processing.
1. Wireless sensor networks consist of distributed sensor nodes that communicate wirelessly to monitor physical or environmental conditions, such as temperature, sound, or pollution levels.
2. The sensor nodes gather and route data back to a central sink/gateway node where the information can be analyzed.
3. Communication protocols and algorithms are required for efficient multi-hop routing of data between sensor nodes and the sink node.
it has a small description about how wireless sensor system network can be applied in various field. A application of leaksge detection is discussed in detail.
INTRODUCTION TO WIRELESS SENSOR NETWORKS.
This powerpoint generally defines Wireless Sensor Networks, the advantages, disadvantages and the general types.
- A wireless sensor network consists of spatially distributed autonomous sensors that monitor conditions like temperature and sound and transmit data to a central location. The networks are bidirectional, enabling control of sensor activity.
- Sensor networks are built from a few to thousands of nodes. Each node contains a sensor connected to a small computer called a mote or sensor node that has limited processing power, memory, radio transceivers, and a battery power source.
- Sensor nodes consume the most power when communicating data over radio frequencies. Batteries are the main power source but energy harvesting is also used. Power constraints is one of the main challenges for wireless sensor networks.
Wireless sensor networks consist of sensors distributed in an ad hoc manner to sense physical phenomena and process the gathered information. They use broadcast communication and have limited power, energy, and computational capabilities compared to traditional networks. Wireless sensor networks can monitor objects, areas, and interactions between objects and spaces through applications in environmental monitoring, precision agriculture, military surveillance, healthcare, and more. They are self-organizing and can operate in extreme conditions, with future applications including smart homes, medical monitoring, traffic management, and industrial/commercial automation.
This document provides an overview of industrial wireless solutions for monitoring and control applications. It discusses the benefits of wireless over wired solutions such as reduced costs and increased flexibility. The document describes the company's product line of wireless transmitters, receivers, gateways, and expansion units. It also outlines common industrial applications such as remote tank monitoring and power plant stack gas monitoring. Key benefits highlighted include cost savings, reliability, security, and ease of installation.
A wireless sensor network(WSN) is a wireless network that is designed using spatially distributed self –governing devices that uses sensors for monitoring physical or environmental conditions.
This document provides an overview of wireless sensor networks, including their applications in various fields such as military, environment, health, home, and automotive. It discusses the key factors influencing sensor network design such as fault tolerance, scalability, and power consumption. It also describes the typical components of sensor nodes, communication architectures, operating systems like TinyOS, and simulators used for wireless sensor networks.
Distributed sensor networks (DSN) consist of multiple sensor nodes that detect conditions and transmit data wirelessly. Each node contains sensors, microprocessors, transceivers, and power sources. DSNs implement a distributed control architecture to improve data collection and provide backup in case nodes fail. They were first developed by DARPA in 1978 and have standards set by groups like IEEE. DSNs are used for military surveillance, environmental monitoring, health applications, and home automation. They are poised to revolutionize various fields due to advantages like scalability, fault tolerance, and ability to operate in harsh environments.
Wireless sensor networks (WSNs) refer to spatially distributed sensors that wirelessly transmit data about the environment such as temperature, sound, and pollution levels. A WSN consists of sensor nodes that contain sensors, processors, memory, transceivers, and power supplies. Sensor nodes form a multi-hop ad-hoc network to send data to a central location. WSNs have applications in military surveillance, environmental monitoring, healthcare, home automation, and more. However, designing WSNs poses challenges related to limited node resources, energy efficiency, scalability, and operating in harsh environments.
Wireless sensor networks are composed of thousands of sensor nodes that can sense, compute, and communicate wirelessly. Each sensor node contains sensing, processing, transceiver, and power units. Sensor nodes monitor conditions like temperature, sound, and pollution. They communicate wirelessly to form a flexible, adaptive network. Wireless sensor networks are used in many applications like healthcare, defense, and environmental monitoring due to advantages like low cost, flexibility, and ease of adding new devices. However, issues like limited battery life, low communication speeds, and interference exist.
An overview of a wireless sensor network communicationphbhagwat
This document provides an overview of wireless sensor network communication architectures and their design challenges. It describes that wireless sensor networks consist of spatially distributed sensors that cooperatively monitor physical conditions. The key components of sensor nodes are described as well as common communication architectures and protocols used. Some examples of wireless sensor network applications are also mentioned such as environmental monitoring, precision agriculture, and health monitoring. Design challenges for wireless sensor networks include energy efficiency, distributed processing, and operating in harsh environments.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms.
The document discusses the benefits of exercise for mental health. It notes that regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise has also been shown to enhance self-esteem and serve as a healthy means of stress management.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive functioning. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
This document discusses using Python to interact with SQLite databases. It provides examples of how to connect to an SQLite database, create tables, insert/update/delete records, and query the database. Key points covered include using the sqlite3 module to connect to a database, getting a cursor object to execute SQL statements, and various cursor methods like execute(), executemany(), fetchone(), fetchall(), commit(), and close(). Example code is given for common SQLite operations like creating a table, inserting records, updating records, deleting records, and selecting records.
The document discusses a scanner called AltaScanner. It mentions that something was scanned with the AltaScanner seven separate times. However, no other details are provided about what was scanned or the purpose and results of the scanning.
1) The document discusses arrays in C programming, including what arrays are, how to declare and initialize one-dimensional arrays, and how to perform common operations like reading, writing, summing, and finding largest elements in arrays.
2) Examples are provided to demonstrate how to write programs to read and display arrays, calculate sums of array elements, and determine other properties of arrays.
3) Key concepts covered include declaring arrays, initializing arrays, accessing array elements, looping through arrays, and performing calculations using the elements of arrays.
The document discusses the benefits of meditation for reducing stress and anxiety. Regular meditation practice can help calm the mind and body by lowering heart rate and blood pressure. Making meditation a part of a daily routine, even if just 10-15 minutes per day, can have mental and physical health benefits over time by helping people feel more relaxed and better able to handle life's stresses.
1) Medium Access Control (MAC) protocols regulate access to shared wireless channels and ensure performance requirements of applications are met. They assemble data into frames, append addressing and error detection, and disassemble received frames.
2) Common MAC protocols include Fixed Assignment (e.g. TDMA), Demand Assignment (e.g. polling), and Random Assignment (e.g. ALOHA, CSMA). Schedule-based MAC protocols avoid contention through resource scheduling while contention-based protocols (e.g. CSMA/CA) allocate resources on demand, risking collisions.
3) The document discusses various MAC protocols for wireless sensor networks and their objectives to minimize energy waste from idle listening, collisions,
More from Deepika,Assistant Professor,PES College of Engineering ,Mandya (8)
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
International Conference on NLP, Artificial Intelligence, Machine Learning an...gerogepatton
International Conference on NLP, Artificial Intelligence, Machine Learning and Applications (NLAIM 2024) offers a premier global platform for exchanging insights and findings in the theory, methodology, and applications of NLP, Artificial Intelligence, Machine Learning, and their applications. The conference seeks substantial contributions across all key domains of NLP, Artificial Intelligence, Machine Learning, and their practical applications, aiming to foster both theoretical advancements and real-world implementations. With a focus on facilitating collaboration between researchers and practitioners from academia and industry, the conference serves as a nexus for sharing the latest developments in the field.
We have compiled the most important slides from each speaker's presentation. This year’s compilation, available for free, captures the key insights and contributions shared during the DfMAy 2024 conference.
Literature Review Basics and Understanding Reference Management.pptxDr Ramhari Poudyal
Three-day training on academic research focuses on analytical tools at United Technical College, supported by the University Grant Commission, Nepal. 24-26 May 2024
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
3. Introduction
• WSNs are collections of compact-size ,relatively inexpensive
computational nodes that measure local environmental
conditions or other parameters and forward such information
to a central point for appropriate processing.
• WSNs nodes(WNs) can sense the environment ,can
communicate with neighboring nodes, and can ,in many
cases, perform basic computations on the data being
collected.
• WSNs support wide range of applications.
3
4. Two categories of WSN’s
• C1WSN(category 1 WSN)
• C2WSN(category 2 WSN)
4
5. Category 1 WSNs (C1WSNs)
• Mesh-based systems
– Multihop radio connectivity among or between
WNs
– Dynamic routing in both the wireless and wireline
portions of the network.
– Ex: Military applications
5
6. Category 1 WSNs
• Consist of hundreds (even thousands) of inexpensive WNs
• WNs have operate in an unattended mode
• Battery: piezo electrically or solar-powered
• End devices may be at more than one radio hop away from a routing or forwarding
node
• The forwarding node is a wireless router that supports dynamic routing
• Wireless routers are often connected over wireless links.
6
7. Category 1 WSNs
The important characterizations are
Sensor nodes can support communications on behalf of other (repeaters)
The forwarding node supports dynamic routing with more than one physical link
to the rest of the network
The radio links are measured in thousands of meters
The forwarding node can support data processing or reduction on behalf of the
sensor nodes
Complex and ‘‘meshy’’ wireless systems
7
9. Cooperative and Non cooperative
Nodes
Two types of behavior by intermediate nodes
Cooperative (when a node forwards information on behalf of another node)
Non cooperative (when a node handles only its own communication) .
9
10. Category 2 WSNs
• Point-to-point or Multipoint-to-point (star based)
single-hop radio connectivity
• Static routing over the wireless network
• Typically only one route from the WNs to the
companion wire line forwarding node
• Residential control systems typically belong to this
category
10
11. Category 2 WSNs
• End devices are one radio hop away from
a terrestrially homed forwarding node.
• Forwarding node (wireless router) is
connected to the terrestrial network via
either landline or a point-to-point
wireless link.
11
12. C2WSN
Important characterizations
• Sensor nodes do not support communications on behalf of other
• Forwarding node supports only static routing to the terrestrial network
• Only one physical link to the terrestrial network present from each node
• Radio link is measured in hundreds of meters
• Forwarding node does not support data processing on behalf of the
sensor nodes
Relativelysimplewirelesssystems
12
14. Applications Categories
• Commercial building control
• Environmental (land, air, sea) and agricultural wireless sensors
• Home automation, including alarms (e.g., an alarm sensor that triggers a call to a
security firm)
• National security applications: chemical, biological, radiological, and nuclear
wireless sensors (sensors for toxic chemicals, explosives, and biological agents)
• Industrial monitoring and control
• Metropolitan operations (traffic, automatic tolls, fire, etc.)
• Military sensors
• Process control
• Wireless automated meter reading and load management
14
15. RANGE OF APPLICATIONS
• Air traffic control
• Area and theater monitoring (military)
• Automatic control of multiple home systems to improve conservation, convenience, and safety
• Automatic meter reading
• Automating control of multiple systems to improve conservation, flexibility, and security
• Automotive sensors and actuators
• Battlefield management
• Biological monitoring for agents
• Biomedical applications
• Borders monitoring (Mexican and Canadian borders)
• Bridge and highway monitoring (safety)
• Capturing highly detailed electric, water, and gas utility usage data
15
16. RANGE OF APPLICATIONS
• Civil engineering applications
• Control of temperature
• Controlling the spread of wild fires
• Defense systems
• Detecting an impulsive event (e.g., a footstep or gunshot) or vehicle (e.g., wheeled or tracked, light
or heavy)
• Earthquake detection
• Electricity load management
• Environmental (land, air, sea) and agricultural wireless sensors
• Environmental control (e.g., tracking soil contamination, habitat monitoring)
• Flexible management of lighting, heating, and cooling systems from anywhere in the home
• Food safety
• Gas, water, and electric meters
16
17. RANGE OF APPLICATIONS
• Habitat monitoring
• Habitat sensing
• Health care
• Home automation, including alarms (e.g., an alarm sensor that triggers a call to a
security firm)
• Home monitoring for chronic and elderly patients (collection of periodic or continuous
data and upload to physicians)
• Home security
• Industrial and building monitoring
17
18. RANGE OF APPLICATIONS
• Industrial and manufacturing automation
• Inventory control
• Localization
• Military vigilance for unknown troop and vehicle activity
• Mobile robotics
• Monitoring for explosives
• Monitoring for toxic chemicals
• Remotely-controlled home heating and lighting
More and More……………..
18
19. Home Control(C2WSN)
Home control applications provide
control, conservation, convenience, and safety
Sensing applications
• Enable management of lighting, heating, and cooling systems
• Highly detailed electric, water, and gas utility usage data
• Embed intelligence to optimize consumption of natural resources
19
20. Home Control
Enable the installation, upgrading, and networking of a home control system
without wires
Enable to configure and run multiple systems from a single remote control
Support the straightforward installation of wireless sensors to monitor a wide
variety of conditions
Facilitate the reception of automatic notification upon detection of unusual
events.
20
22. Home Control (Medical Sensor)
• Body-worn medical sensors (e.g., heartbeat sensors)
• Battery-operated devices with network beacons occurring
every few seconds
• Worn by home-resident elderly or people with other medical
conditions
• Sensors have two ongoing processes:
– Heartbeat time logging
– Transmission of heart rate and other information (instantaneous
and average heart rate, body temperature, and battery voltage) 22
23. Building Automation
• Wireless lighting control can easily be accomplished with
ZigBee technology in C2WSNs with
– Dimmable ballasts
A solid-state ballast that can provide variable light output in
response to a signal (from a photo sensor)
Benefits : reduces electricity use , reduces flicker, weight and
noise and generates less heat
– Controllable light switches
23
24. Building Automation
Sensing applications enable
• Centralize management of lighting, heating, cooling, and security
• Reduce energy expenses through optimized Heating, ventilation, and air-
conditioning (HVAC).
• Allocate utility costs equitably based on actual consumption
• Extension and upgrading of building infrastructure with minimal effort
• Network and integrate data from multiple access control points
• Deploy wireless monitoring networks to enhance perimeter protection
24
25. Building Automation
• Wireless motes installed in individual lighting fixtures in conjunction
with a remote wireless switch capable of controlling the light fixtures
• Integrated sensor communication and i.e., Multiple sensing of
temperature, light, sound, flow, and localization
• Wireless network interface allows the node to be self-contained and to
operate independently
• Support building control applications software
25
27. Buildings Energy Scavenging
• Environmental control for buildings energy scavenging
– Airflow measurement technology :
• Use of sensor networks for controlling indoor temperature
• Multi sensor and single-actuator control of temperature
• Sensor network that has at least one sensor in each space
• Information from a WSN to control multiple spaces in a building
• Reduce energy consumption and improve comfort at the same time
• The performance improvement is achieved without changing the
actuation
27
28. RFID (Radio Sensor)
• RFID tagging is an ID system that uses small radio frequency identification
devices for identification and tracking purposes.
• An RFID tagging system includes
– Tag
– Read/write device
– Host system application for data collection, processing, and transmission.
28
30. RFID (Radio Sensor)
Applications:
Package tracking, security, banking, control.
Example:
Airbus’s A380 airplane is equipped with about 10,000 RFID chips
Plane has passive RFID chips on removable parts ( passenger
seats and plane components)
Benefits of RFID tagging of airplane parts
Reducing the time for aircraft-inspection reports
Optimizing maintenance operations.
30
31. WSN applications(C1WSN)
• Military sensor networks to detect and gain information
– Enemy movements
– Explosions
– Phenomena of interest
• Law enforcement and national security tracking or nefarious substance monitoring
• Sensor networks to detect and characterize
– Chemical
– Biological
– Radiological
– Nuclear
– Explosive (CBRNE) attacks and material
• Sensor networks to detect and monitor environmental changes in
– Plains
– Forests
– Oceans 31
32. WSN applications(C1WSN)
Wireless sensor networks
• To monitor vehicle traffic on highways
• To provide security in shopping malls, parking garages
• To spot unoccupied parking place parking lot
• Borders monitoring and satellite uplinks
32
33. Sensor and Robots
Intel envisions :
• Mobile robots acting as gateways (sink) into wireless sensor
networks
• Robots embody sensing, actuation, and basic robotics
functions
• Two questions of interest
• Can a mobile robot act as a gateway into a wireless sensor network?
• Can sensor networks take advantage of a robot’s mobility and
intelligence?
33
34. Sensor and Robots
To affect this convergence
• Inexpensive standards-based hardware
• Open-source operating systems
• Connectivity modules are required
– Intel XScale microprocessors
– Intel Centrino mobile technology
34
35. Sensor and Robots
• Major issue : communication between the robot and the sensor network
• Sensor network equipped with IEEE 802.11 capabilities to bridge the gap between robotics and
wireless networks
• Intel demonstrated with few motes equipped with 802.11 wireless capabilities added to a
sensor network to act as wireless hubs (switch )
• Other motes in the network then utilize each other as links to reach the 802.11-equipped hubs
• The hubs forward the data packets to the main 802.11-capable gateway ( PC or laptop).
• Using some motes as hubs
– Reduces the number of hops that any one data packet has to make to reach the main
gateway,
– Reduces power consumption across the sensor network.
35
36. Sensors in a Vineyard(Intel)
• Small sensors in a vineyard in Oregon to monitor microclimates
• Sensors measured temperature, humidity, and other factors to monitor the growing
cycle of the grapes
• Sensors transmitted the data via Multihop to reached a gateway
• Data interpreted at gateway and used to help prevent
– Frostbite (Injury to any part of the body after excessive exposure to extreme cold) ,
– Mold (Microscopic fungi ) and other agricultural problems
36
37. Sensors in semiconductor manufacturing fab
At Intel’s semiconductor fabs to predict machines failure ( about to )
Thousands of sensors track vibrations coming from various pieces of equipment
Sensor data manually gathered from each node periodically
(schedule determined by the expected failure rate of the equipment)
Managers determine the particular signature that a well functioning machine should
have
Application of sensor network
Networking the sensors could make the process more efficient and cost-effective.
Intel plans to make use of the mote technology to build an application that acquires
data automatically
37
39. Civil and Environmental Engineering Applications
• Sensor technology applicable for
– Buildings, bridges and other structures
• To develop ‘‘smart structures’’
– To self-diagnose potential problems
– Self-prioritize requisite repairs
39
40. WSN for Earthquake Zones
• Routine mild tremors
– May not cause visible damage
– Give rise to hidden cracks that could eventually fail during a
higher-magnitude quake
• After a mild earthquake
– Building’s true structural condition may not be extensively visible
without some ‘‘below-the-skin’’ measurement
– Dynamic response sensing sensors
40
41. Smart Dust motes
Developed by UC–Berkeley engineers
– Tiny
– Inexpensive
– Battery-powered matchbox-sized WNs
– Operating on TinyOS are designed
– Sense number of factors
• Light & Temperature (for energy-saving applications)
• Dynamic response (for civil engineering analysis)
41
44. Classification Factors
Size of the system
Number of sensors used
Average (and/or maximum) distance (in hops)
of the sensors to the wired infrastructure
Distribution of the sensor nodes
44
45. ANOTHER TAXONOMY OF WSN
TECHNOLOGY
Three types of WSN system (technology) that have been described in are:
1. Nonpropagating WSN systems
2. Deterministic routing WSN systems
a. Aggregating
b. Nonaggregating systems
3. Self-configurable and self-organizing WSN systems
a. Aggregating
b. Nonaggregating systems
45
46. Nonpropagating WSN
No support of dynamic routing to end systems
Close proximity (one hop) to the wired infrastructure
Collect and report sensor measurements to nodes connected to
the wired network intern to the end system
Manually configurable and highly deterministic in deployment
Environmental sensors deployed in buildings belong to this
category.
46
47. Deterministic routing WSN
o The wired and wireless infrastructures play an active
role in routing packets.
o The WNs route - wireless multi hops
o The routes to the wired infrastructure
o Deterministic
o Configured manually
o The number of nodes usually small.
47
48. Aggregating systems
WNs aggregated and forwarded Information received from
‘‘downstream’’
Intermediary nodes - ability to fuse the information
received from downstream sources
Weather monitoring systems are examples of aggregating
WSNs
48
49. Non aggregating systems
Information gathered by source node is independent and is transmitted
separately.
Toll-badge-reading (Tag)systems are examples of non aggregating WSNs
Nodes are one hop away from the wired node
No in-network aggregation issue.
Aggregation functionality is performed in the
wired infrastructure
gateway
No specialized aggregating functionality to be embedded into the WSN
49
50. Self-configurable and Self organize systems
WNs need to self organize themselves (initially or as time goes by) into a
connected network
Nondeterministic in topological deployment
Number of nodes can be from hundreds to hundreds of thousands
Gateway WNs have connectivity to the wired infrastructure for transferring
information to the end systems
Security network (a target-tracking ) system is an example of a deterministic and
configurable systems ( self-configurable )WSN
In self-configurable WSNs, the nodes may also aggregate data
50