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network lifetime. However, this duty cycling may result in high network latency, routing overhead, and neighbor discovery delays due to asynchronous sleep and wake-up scheduling. These limitations call for a countermeasure for duty-cycled wireless sensor networks which should minimize routing information, routing traffic load, and energy consumption. Researchers from
Sungkyunkwan University have proposed a lightweight non-increasing delivery-latency interval routing referred as LNDIR. This scheme can discover minimum latency routes at each non-increasing delivery-latency interval instead of each time slot. Simulation experiments demonstrated the validity of this novel approach in minimizing routing information stored at each sensor. Furthermore, this novel routing can also guarantee the minimum delivery latency from each source to the sink. Performance improvements of up to 12-fold and 11-fold are observed in terms of routing traffic load reduction and energy efficiency, respectively, as compared to existing schemes.
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can measure averages or directionality for example of readings from other nodes. For example, in sensing and monitoring applications, it is generally the case that neighboring sensor nodes monitoring an environmental feature typically register similar values. This kind of data redundancy due to the spatial correlation between sensor observations inspires techniques for in-network data aggregation and mining. Aggregation reduces the amount of network traffic which helps to reduce energy consumption on sensor nodes. Recently, it has been found that network gateways also play an important role in improving energy efficiency of sensor nodes by scheduling more resources for the nodes with more critical energy efficiency need and advanced energy efficient scheduling algorithms need to be implemented at network gateways for the improvement of the overall network energy efficiency.
378:, since more sensors both improves the detection rate and reduces false alarms. WATS sensors could be deployed in permanent positions or mounted in vehicles for mobile protection of specific locations. One barrier to the implementation of WATS is the size, weight, energy requirements and cost of currently available wireless sensors. The development of improved sensors is a major component of current research at the Nonproliferation, Arms Control, and International Security (NAI) Directorate at LLNL.
231:). However, sensors for gases and particulate matter suffer from high unit-to-unit variability, cross-sensitivities, and (concept) drift. Moreover, the quality of data is currently insufficient for trustworthy decision-making, as field calibration leads to unreliable measurement results, and frequent recalibration might be required. A possible solution could be blind calibration or the usage of mobile references.
792:. Such platforms simplify online collaboration between users over diverse data sets ranging from energy and environment data to that collected from transport services. Other services include allowing developers to embed real-time graphs & widgets in websites; analyse and process historical data pulled from the data feeds; send real-time alerts from any datastream to control scripts, devices and environments.
892:" which was used for detection of sophisticated attacks, like blackhole or wormhole, which degrade the throughput of large networks to close-to-zero. This primitive has since been used by many researchers and commercial wireless packet sniffers. This was subsequently refined for more sophisticated attacks such as with collusion, mobility, and multi-antenna, multi-channel devices.
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187:, or other similar devices. Body-area networks can collect information about an individual's health, fitness, and energy expenditure. In health care applications the privacy and authenticity of user data has prime importance. Especially due to the integration of sensor networks, with IoT, the user authentication becomes more challenging; however, a solution is presented in recent work.
63:. Modern networks are bi-directional, both collecting data and enabling control of sensor activity. The development of these networks was motivated by military applications such as battlefield surveillance. Such networks are used in industrial and consumer applications, such as industrial process monitoring and control and machine health monitoring and agriculture.
685:, for two reasons. First, wireless sensor networks are typically deployed with a particular application in mind, rather than as a general platform. Second, a need for low costs and low power leads most wireless sensor nodes to have low-power microcontrollers ensuring that mechanisms such as virtual memory are either unnecessary or too expensive to implement.
179:
Environment-embedded systems employ sensors contained in the environment. Possible applications include body position measurement, location of persons, overall monitoring of ill patients in hospitals and at home. Devices embedded in the environment track the physical state of a person for continuous health diagnosis, using as input the data from a network of
371:. WATS would not use a centralized computer for analysis because researchers found that factors such as latency and available bandwidth tended to create significant bottlenecks. Data processed in the field by the network itself (by transferring small amounts of data between neighboring sensors) is faster and makes the network more scalable.
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are assumed to be unsecured with limited available energy, while the base station is assumed to be secure with unlimited available energy. Aggregation complicates the already existing security challenges for wireless sensor networks and requires new security techniques tailored specifically for these
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Reprogramming is the process of updating the code on the sensor nodes. The most feasible form of reprogramming is remote reprogramming whereby the code is disseminated wirelessly while the nodes are deployed. Different reprogramming protocols exist that provide different levels of speed of operation,
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Online collaborative sensor data management platforms are on-line database services that allow sensor owners to register and connect their devices to feed data into an online database for storage and also allow developers to connect to the database and build their own applications based on that data.
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sensor nodes. There are an increasing number of small companies producing WSN hardware and the commercial situation can be compared to home computing in the 1970s. Many of the nodes are still in the research and development stage, particularly their software. Also inherent to sensor network adoption
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There are studies that show that using sensors for incident monitoring improve in a great way the response of firefighters and police to an unexpected situation. For an early detection of incidents we can use acoustic sensors to detect a spike in the noise of the city because of a possible accident,
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To reduce communication costs some algorithms remove or reduce nodes' redundant sensor information and avoid forwarding data that is of no use. This technique has been used, for instance, for distributed anomaly detection or distributed optimization. As nodes can inspect the data they forward, they
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As for the distributed filtering over distributed sensor network. the general setup is to observe the underlying process through a group of sensors organized according to a given network topology, which renders the individual observer estimates the system state based not only on its own measurement
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The architecture of the
Wikisensing system describes the key components of such systems to include APIs and interfaces for online collaborators, a middleware containing the business logic needed for the sensor data management and processing and a storage model suitable for the efficient storage and
243:
has started. The nodes can be equipped with sensors to measure temperature, humidity and gases which are produced by fire in the trees or vegetation. The early detection is crucial for a successful action of the firefighters; thanks to
Wireless Sensor Networks, the fire brigade will be able to know
256:
detection system makes use of a wireless sensor network to detect the slight movements of soil and changes in various parameters that may occur before or during a landslide. Through the data gathered it may be possible to know the impending occurrence of landslides long before it actually happens.
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first motivated and proposed a radio connectivity based system for localization of wireless sensor networks. Subsequently, such localization systems have been referred to as range free localization systems, and many localization systems for wireless sensor networks have been subsequently proposed
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Lifetime maximization: Energy/Power
Consumption of the sensing device should be minimized and sensor nodes should be energy efficient since their limited energy resource determines their lifetime. To conserve power, wireless sensor nodes normally power off both the radio transmitter and the radio
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Energy is the scarcest resource of WSN nodes, and it determines the lifetime of WSNs. WSNs may be deployed in large numbers in various environments, including remote and hostile regions, where ad hoc communications are a key component. For this reason, algorithms and protocols need to address the
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might vary in size from a shoebox to (theoretically) a grain of dust, although microscopic dimensions have yet to be realized. Sensor node cost is similarly variable, ranging from a few to hundreds of dollars, depending on node sophistication. Size and cost constraints constrain resources such as
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Wireless sensor networks also are used for the collection of data for monitoring of environmental information. This can be as simple as monitoring the temperature in a fridge or the level of water in overflow tanks in nuclear power plants. The statistical information can then be used to show how
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If a centralized architecture is used in a sensor network and the central node fails, then the entire network will collapse, however the reliability of the sensor network can be increased by using a distributed control architecture. Distributed control is used in WSNs for the following reasons:
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Wireless sensor networks are composed of low-energy, small-size, and low-range unattended sensor nodes. Recently, it has been observed that by periodically turning on and off the sensing and communication capabilities of sensor nodes, we can significantly reduce the active time and thus prolong
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is traditionally used to provide end to end confidentiality in wireless sensor network, the aggregators in a secure data aggregation scenario need to decrypt the encrypted data to perform aggregation. This exposes the plaintext at the aggregators, making the data vulnerable to attacks from an
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Macro-programming is a term coined by Matt Welsh. It refers to programming the entire sensor network as an ensemble, rather than individual sensor nodes. Another way to macro-program a network is to view the sensor network as a database, which was popularized by the TinyDB system developed by
843:
Sensors and devices used in wireless sensor networks are state-of-the-art technology with the lowest possible price. The sensor measurements we get from these devices are therefore often noisy, incomplete and inaccurate. Researchers studying wireless sensor networks hypothesize that much more
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monitoring involves analyzing water properties in dams, rivers, lakes and oceans, as well as underground water reserves. The use of many wireless distributed sensors enables the creation of a more accurate map of the water status, and allows the permanent deployment of monitoring stations in
44:) refer to networks of spatially dispersed and dedicated sensors that monitor and record the physical conditions of the environment and forward the collected data to a central location. WSNs can measure environmental conditions such as temperature, sound, pollution levels, humidity and wind.
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There are several types of sensor networks for medical applications: implanted, wearable, and environment-embedded. Implantable medical devices are those that are inserted inside the human body. Wearable devices are used on the body surface of a human or just at close proximity of the user.
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Network localization refers to the problem of estimating the location of wireless sensor nodes during deployments and in dynamic settings. For ultra-low power sensors, size, cost and environment precludes the use of Global
Positioning System receivers on sensors. In 2000, Nirupama Bulusu,
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operates at 915 MHz and in the EU 868 MHz has been widely used but these have a lower data rate (typically 50 kbit/s). The IEEE 802.15.4 working group provides a standard for low power device connectivity and commonly sensors and smart meters use one of these standards for
722:
with run-to-completion semantics. When an external event occurs, such as an incoming data packet or a sensor reading, TinyOS signals the appropriate event handler to handle the event. Event handlers can post tasks that are scheduled by the TinyOS kernel some time later.
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The 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. Other special components in
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At present, agent-based modeling and simulation is the only paradigm which allows the simulation of complex behavior in the environments of wireless sensors (such as flocking). Agent-based simulation of wireless sensor and ad hoc networks is a relatively new paradigm.
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There have been important innovations in securing wireless sensor networks. Most wireless embedded networks use omni-directional antennas and therefore neighbors can overhear communication in and out of nodes. This was used this to develop a primitive called
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Monitoring the quality and level of water includes many activities such as checking the quality of underground or surface water and ensuring a country's water infrastructure for the benefit of both human and animal. It may be used to protect the wastage of water.
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reliability, energy expenditure, requirement of code resident on the nodes, suitability to different wireless environments, resistance to DoS, etc. Popular reprogramming protocols are Deluge (2004), Trickle (2004), MNP (2005), Synapse (2008), and Zephyr (2009).
937:(OGC) is specifying standards for interoperability interfaces and metadata encodings that enable real time integration of heterogeneous sensor webs into the Internet, allowing any individual to monitor or control wireless sensor networks through a web browser.
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adversary. Similarly an aggregator can inject false data into the aggregate and make the base station accept false data. Thus, while data aggregation improves energy efficiency of a network, it complicates the existing security challenges.
165:
Area monitoring is a common application of WSNs. In area monitoring, the WSN is deployed over a region where some phenomenon is to be monitored. A military example is the use of sensors to detect enemy intrusion; a civilian example is the
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Traditional layered approach cannot share different information among different layers, which leads to each layer not having complete information. The traditional layered approach cannot guarantee the optimization of the entire
335:
Wireless sensor networks can be used to monitor the condition of civil infrastructure and related geo-physical processes close to real time, and over long periods through data logging, using appropriately interfaced sensors.
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Because of the interference between the different users, access conflicts, fading, and the change of environment in the wireless sensor networks, traditional layered approach for wired networks is not applicable to wireless
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Infrastructure-less architecture (i.e. no gateways are included, etc.) and inherent requirements (i.e. unattended working environment, etc.) of WSNs might pose several weak points that attract adversaries. Therefore,
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Saleem, Kashif; Fisal, Norsheila; Hafizah, Sharifah; Kamilah, Sharifah; Rashid, Rozeha; Baguda, Yakubu (2009). "Cross layer based biological inspired self-organized routing protocol for wireless sensor network".
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would be useless (or less effective) for WSNs. Hence, lack of security mechanisms would cause intrusions towards those networks. These intrusions need to be detected and mitigation methods should be applied.
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information can be extracted from hundreds of unreliable measurements spread across a field of interest than from a smaller number of high-quality, high-reliability instruments with the same total cost.
385:
Military
Research and Development Subcommittee on October 1, 1997, during a hearing on nuclear terrorism and countermeasures. On August 4, 1998, in a subsequent meeting of that subcommittee, Chairman
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through a gateway. The
Gateway acts as a bridge between the WSN and the other network. This enables data to be stored and processed by devices with more resources, for example, in a remotely located
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Wireless sensor networks have been used to monitor various species and habitats, beginning with the Great Duck Island
Deployment, including marmots, cane toads in Australia and zebras in Kenya.
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133:
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Kiran
Maraiya, Kamal Kant, Nitin Gupta "Wireless Sensor Network: A Review on Data Aggregation" International Journal of Scientific & Engineering Research Volume 2 Issue 4, April 2011.
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Aghdam, Shahin
Mahdizadeh; Khansari, Mohammad; Rabiee, Hamid R; Salehi, Mostafa (2014). "WCCP: A congestion control protocol for wireless multimedia communication in sensor networks".
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in the sense that they rely on wireless connectivity and spontaneous formation of networks so that sensor data can be transported wirelessly. WSNs monitor physical conditions, such as
203:
There are many applications in monitoring environmental parameters, examples of which are given below. They share the extra challenges of harsh environments and reduced power supply.
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which provides long range low power wireless connectivity for devices, which has been used in smart meters and other long range sensor applications. Wi-SUN connects devices at home.
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The Wide Area Tracking System (WATS) is a prototype network for detecting a ground-based nuclear device such as a nuclear "briefcase bomb." WATS is being developed at the
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is a big concern when WSNs are deployed for special applications such as military and healthcare. Owing to their unique characteristics, traditional security methods of
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can connect sensors operating at 2.4 GHz with a data rate of 250 kbit/s. Many use a lower frequency to increase radio range (typically 1 km), for example
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Bosman, H. H. W. J.; Iacca, G; Tejada, A.; Wörtche, H. J.; Liotta, A. (2015-12-01). "Ensembles of incremental learners to detect anomalies in ad hoc sensor networks".
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Cam, H; Ozdemir, S Nair, P Muthuavinashiappan, D (October 2003). "ESPDA: Energy-efficient and Secure Pattern-based Data Aggregation for wireless sensor networks".
509:(QoS), etc. Sensor nodes can be imagined as small computers which are extremely basic in terms of their interfaces and their components. They usually consist of a
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Wireless sensor networks have been developed for machinery condition-based maintenance (CBM) as they offer significant cost savings and enable new functionality.
66:
A WSN is built of "nodes" – from a few to hundreds or thousands, where each node is connected to other sensors. Each such node typically has several parts: a
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Cross-layer is becoming an important studying area for wireless communications. In addition, the traditional layered approach presents three main problems:
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Magno, M.; Boyle, D.; Brunelli, D.; O'Flynn, B.; Popovici, E.; Benini, L. (2014). "Extended Wireless Monitoring Through Intelligent Hybrid Energy Supply".
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Apte, J.S.; Messier, K.P.; Gani, S.; Brauer, M.; Kirchstetter, T.W.; Lunden, M.M.; Marshall, J.D.; Portier, C.J.; Vermeulen, R.C.H.; Hamburg, S.P. (2017).
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356:(LLNL). WATS would be made up of wireless gamma and neutron sensors connected through a communications network. Data picked up by the sensors undergoes
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Kumar, Vimal; Sanjay K. Madria (August 2012). "Secure Hierarchical Data Aggregation in Wireless Sensor Networks: Performance Evaluation and Analysis".
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Wireless sensors can be placed in locations difficult or impossible to reach with a wired system, such as rotating machinery and untethered vehicles.
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Bosman, H. H. W. J.; Liotta, A.; Iacca, G.; Wörtche, H. J. (October 2013). "Anomaly Detection in Sensor Systems Using Lightweight Machine Learning".
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Bosman, H. H. W. J.; Iacca, G.; Wörtche, H. J.; Liotta, A. (December 2014). "Online Fusion of Incremental Learning for Wireless Sensor Networks".
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Feinberg, S.; Williams, R.; Hagler, G.S.W.; Rickard, J.; Garver, D.; Harshfield, G.; Stauffer, P.; Mattson, E.; Judge, R.; Garvey, S. (2018).
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The data gathered from wireless sensor networks is usually saved in the form of numerical data in a central base station. Additionally, the
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Hassan, T. A. H.; Selim, G.; Sadek, R. (2015). "A novel energy efficient vice Cluster Head routing protocol in Wireless Sensor Networks".
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Tiwari, Ankit; et al. (2007). "Energy-efficient wireless sensor network design and implementation for condition-based maintenance".
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is a newly developed OS for wireless sensor networks, which provides UNIX-like abstraction and support for the C programming language.
281:, like floods. Wireless nodes have been deployed successfully in rivers, where changes in water levels must be monitored in real time.
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Bosman, H. H. W. J.; Liotta, A.; Iacca, G.; Wörtche, H. J. (December 2013). "Online Extreme Learning on Fixed-Point Sensor Networks".
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K. Saleem; N. Fisal & J. Al-Muhtadi (2014). "Empirical studies of bio-inspired self-organized secure autonomousRouting protocol".
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FrancescoMario, Di; K, DasSajal; AnastasiGiuseppe (2011-08-01). "Data Collection in Wireless Sensor Networks with Mobile Elements".
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1480:"J.K.Hart and K. Martinez, "Environmental Sensor Networks: A revolution in the earth system science?", Earth-Science Reviews, 2006"
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for wireless sensor network nodes are typically less complex than general-purpose operating systems. They more strongly resemble
534:
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Xenakis, A.; Foukalas, F.; Stamoulis, G. (October 2015). "Minimum weighted clustering algorithm for wireless sensor networks".
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Sauce, O.; Hasenfratz, D.; Thiele, L. (2015). "Reducing multi-hop calibration errors in large-scale mobile sensor networks".
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360:, which converts the information into easily interpreted forms; this data fusion is the most important aspect of the system.
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the sensor network rather than at a centralized computer and is performed by a specially developed algorithm based on
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systems have been working. The advantage of WSNs over conventional loggers is the "live" data feed that is possible.
4047:
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706:, is perhaps the first operating system specifically designed for wireless sensor networks. TinyOS is based on an
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17:
963:. were the first few works discussing techniques for secure data aggregation in wireless sensor networks.
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Przydatek, Bartosz; Dawn Song; Adrian Perrig (2003). "SIA: Secure information aggregation in sensor networks".
2053:"Psychoacoustic Annoyance Implementation With Wireless Acoustic Sensor Networks for Monitoring in Smart Cities"
1005:
1000:
596:. A wireless wide area network used primarily for low-power devices is known as a Low-Power Wide-Area Network (
518:
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So the cross-layer can be used to make the optimal modulation to improve the transmission performance, such as
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energy, memory, computational speed and communications bandwidth. The topology of a WSN can vary from a simple
2711:"LNDIR: A lightweight non-increasing delivery-latency interval-based routing for duty-cycled sensor networks"
1376:
3574:
128:, wireless sensor networks are an active research area supporting many workshops and conferences, including
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Tony O'Donovan; John O'Donoghue; Cormac Sreenan; David Sammon; Philip O'Reilly; Kieran A. O'Connor (2009).
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Two main security challenges in secure data aggregation are confidentiality and integrity of data. While
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in cities can vary a lot. Therefore, it is of interest to have higher temporal and spatial resolution of
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Network simulators like Opnet, Tetcos NetSim and NS can be used to simulate a wireless sensor network.
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Iacca, G. (2018). "Distributed optimization in wireless sensor networks: an island-model framework".
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223:. For research purposes, wireless sensor networks have been deployed to monitor the concentration of
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2015 IEEE Seventh International Conference on Intelligent Computing and Information Systems (ICICIS)
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for sensor networks. However, such operating systems are often designed with real-time properties.
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2584:"Parameter Self-Configuration and Self-Adaptation in Industrial Wireless Sensor-Actuator Networks"
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Balzano, L.; Nowak, R. (2008). "Blind Calibration of Networks of Sensors: Theory and Algorithms".
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There is also no centralised body to allocate the resources and they have to be self organized.
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The traditional layered approach does not have the ability to adapt to the environmental change.
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Wireless sensor networks are used to monitor wine production, both in the field and the cellar.
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2945:"LITEWORP: A Lightweight Countermeasure for the Wormhole Attack in Multihop Wireless Networks"
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based networks are routers, designed to compute, calculate and distribute the routing tables.
2537:"Reliable Kalman Filtering with Conditionally Local Calculations in Wireless Sensor Networks"
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Proceedings of the 14th International Conference on Information Processing in Sensor Networks
417:
106:
82:
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1579:"Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado"
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Peiris, V. (2013). "Highly integrated wireless sensing for body area network applications".
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3072:. Special Issue on Big Data Inspired Data Sensing, Processing and Networking Technologies.
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2092:"A Wireless Sensor Network Deployment for Rural and Forest Fire Detection and Verification"
2007:
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1505:"High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data"
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administration to a subsistence level and that the program had been poorly re-organized.
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81:, an electronic circuit for interfacing with the sensors and an energy source, usually a
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K Shahzad, Muhammad; Nguyen, Dang Tu; Zalyubovskiy, Vyacheslav; Choo, Hyunseung (2018).
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scenarios. Providing security to aggregate data in wireless sensor networks is known as
739:, is an OS which uses a simpler programming style in C while providing advances such as
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2831:"A Novel Agent-Based Simulation Framework for Sensing in Complex Adaptive Environments"
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and LTE-M can connect up to millions of sensors and devices using cellular technology.
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Hu, Lingxuan; David Evans (January 2003). "Secure aggregation for wireless networks".
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2023 7th International Conference on Computing Methodologies and Communication (ICCMC)
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529:), and a power source usually in the form of a battery. Other possible inclusions are
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Bosman, H. H. W. J.; Iacca, G.; Tejada, A.; Wörtche, H. J.; Liotta, A. (2017-01-01).
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Proceedings of the 1st international conference on Embedded networked sensor systems
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1248:"Wireless sensor networks have potential in health care and agriculture, says study"
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Li, Wangyan; Wang, Zidong; Wei, Guoliang; Ma, Lifeng; Hu, Jun; Ding, Derui (2015).
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is the use of very low power methods for radio communication and data acquisition.
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2492:"Extending the Lifespan of Wireless Sensor Networks using Graph Theory Approaches"
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There are several wireless standards and solutions for sensor node connectivity.
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2389:"Cross-layer energy-aware topology control through Simulated Annealing for WSNs"
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Wireless sensor networks can be effective in preventing adverse consequences of
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Spie (2013). "Vassili Karanassios: Energy scavenging to power remote sensors".
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3309:"Spatial anomaly detection in sensor networks using neighborhood information"
3285:
3099:
3054:
3013:
2727:
2710:
2560:
2365:
2292:
1603:
1361:
1324:
Parametric Analog Signal Amplification Applied to Nanoscale CMOS Technologies
1197:
1095:
421:
357:
265:
224:
212:
184:
3573:
Chalermek Intanagonwiwat, Deborah Estrin, Ramesh Govindan, John Heidemann, "
3029:"A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks"
2636:
1756:
1678:
1529:
1504:
1140:
3819:
3360:
2815:
2418:
2293:
2135:
1834:
1622:
1538:
1465:
1215:
1113:
1025:
744:
736:
703:
390:
306:
220:
180:
99:
3633:
3486:
3204:
3163:
3045:
3028:
2772:"WikiSensing: An Online Collaborative Approach for Sensor Data Management"
2213:"THE WORLD LEADER IN VIBRATION HARVESTER POWERED WIRELESS SENSING SYSTEMS"
753:
is a more recent real-time OS including similar functionality to Contiki.
269:
locations of difficult access, without the need of manual data retrieval.
2949:
2005 International Conference on Dependable Systems and Networks (DSN'05)
2159:"Israeli Tech Firm Rolls Out Tracking Devices the Size of Postage Stamps"
1859:"A national strategy against terrorism using weapons of mass destruction"
1719:
1164:"Wireless Sensor/Actuator Network Design for Mobile Control Applications"
955:
567:
463:
386:
240:
94:
70:
52:
3575:
Impact of Network Density on Data Aggregation in Wireless SensorNetworks
3527:
3335:
3213:
3090:
2956:
2217:
THE WORLD LEADER IN VIBRATION HARVESTER POWERED WIRELESS SENSING SYSTEMS
1823:"Monitoring High-Quality Wine Production using Wireless Sensor Networks"
1062:"Advances in Smart Environment Monitoring Systems Using IoT and Sensors"
771:
239:
A network of Sensor Nodes can be installed in a forest to detect when a
3953:
3771:
3122:
2796:
2028:
967:
928:
854:
526:
216:
3428:"Hybrid energy aware clustered protocol for IoT heterogeneous network"
2921:
2116:
1866:
1446:
1086:
625:, many other proposals have been made to provide sensor connectivity.
4020:
International Conference on Information Processing in Sensor Networks
3963:
3877:
3755:
2875:
1188:
411:
253:
167:
148:. As of 2010, wireless sensor networks had deployed approximately 120
911:
To provide nodes with backup in case of failure of the central node.
3910:
3897:
3882:
3260:
3115:
2013 IEEE International Conference on Systems, Man, and Cybernetics
2850:
2002:
1428:
688:
It is therefore possible to use embedded operating systems such as
498:
60:
2990:"A survey of intrusion detection in wireless network applications"
3872:
3854:
3791:
3740:
3720:
3705:
3700:
3682:
3520:
2012 IEEE 13th International Conference on Mobile Data Management
2738:
Material was copied from this source, which is available under a
1552:
1298:
Wireless sensor networks: technology, protocols, and applications
1010:
761:
757:
740:
732:
550:
110:
3156:
2013 IEEE 13th International Conference on Data Mining Workshops
1162:
Xia, Feng; Tian, Yu-Chu; Li, Yanjun; Sun, Youxian (2007-10-09).
3920:
3829:
3824:
3715:
3692:
3607:
3476:
2906:"GPS-less low cost outdoor localization for very small devices"
2708:
1126:
778:
726:
699:
617:
613:
538:
228:
3624:
Secure Data Aggregation in Wireless Sensor Networks: A *Survey
3565:
Chain-based Gateway nodes routing for energy efficiency in WSN
2588:
IEEE INFOCOM 2019 - IEEE Conference on Computer Communications
1820:
1777:
1295:
838:
756:
PreonVM is an OS for wireless sensor networks, which provides
3915:
3796:
3786:
3766:
2734:
2629:
Proceedings of the 19th Panhellenic Conference on Informatics
2351:
1821:
Anastasi, G.; Farruggia, O.; Lo Re, G.; Ortolani, M. (2009).
1576:
1273:
Fundamentals of wireless sensor networks: theory and practice
693:
630:
597:
130:
International Workshop on Embedded Networked Sensors (EmNetS)
67:
56:
3618:
1827:
2009 42nd Hawaii International Conference on System Sciences
3887:
3814:
3776:
2904:
Bulusu, Nirupama; Heidemann, John; Estrin, Deborah (2000).
2182:
689:
626:
451:
436:
Power consumption constraints for nodes using batteries or
3563:
Amir Hozhabri; Mohammadreza Eslaminejad; Mitra Mahrouyan,
3197:
2014 IEEE International Conference on Data Mining Workshop
2942:
2436:
389:
stated that research funding for WATS had been cut by the
3363:
Proceedings of IEEE Sensors 2003 (IEEE Cat. No.03CH37498)
2241:
2212:
1384:. Pervasive Computing Technologies for Healthcare, 2009.
1270:
782:
3306:
3194:
3153:
3112:
3067:
2916:(5). IEEE Personal Communications, October 2000: 28–34.
2753:"PreonVM – Virtual maschine for wireless sensor devices"
2626:
2386:
2490:
Janakiram, Kottnana; Reginald, P. Joshua (2023-02-23).
1412:"An Authentication Protocol for Future Sensor Networks"
1230:"Wireless sensor networks for battlefield surveillance"
537:, and possibly secondary communication interface (e.g.
440:. Examples of suppliers are ReVibe Energy and Perpetuum
2740:
Creative Commons Attribution 4.0 International License
3517:
3464:
Workshop on Security and Assurance in Ad Hoc Networks
2903:
1668:
1502:
772:
Online collaborative sensor data management platforms
513:
with limited computational power and limited memory,
2715:
International Journal of Distributed Sensor Networks
450:
Some mobility of nodes (for highly mobile nodes see
2943:Khalil, Issa; Bagchi Saurabh; Shroff, N.B. (2005).
1986:"INRISCO: INcident monitoRing in Smart COmmunities"
1898:. Federation of American Scientists. Archived from
469:
Ability to withstand harsh environmental conditions
1275:. John Wiley and Sons. pp. 168–183, 191–192.
1060:Ullo, Silvia Liberata; Sinha, G. R. (2020-05-31).
922:
27:Group of spatially dispersed and dedicated sensors
2489:
2387:Xenakis, A.; Foukalas, F.; Stamoulis, G. (2016).
1935:. Science & Technology Review. Archived from
1865:. Science & Technology Review. Archived from
402:or use termic sensors to detect a possible fire.
211:Experiments have shown that personal exposure to
4039:
2667:
2455:"NB-IOT vs. LoRa vs. Sigfox, LINKLabs, Jan 2017"
2296:; Jens Zander; Ki Won Sung; Ben Slimane (2016).
1378:A Context Aware Wireless Body Area Network (BAN)
584:In many applications, a WSN communicates with a
420:, WSN:s can be cost-efficiently applied also in
244:when a fire is started and how it is spreading.
4026:Conference on Embedded Networked Sensor Systems
4014:European Conference on Wireless Sensor Networks
3583:Wireless Sensor Networks: A Systems Perspective
1409:
521:(including specific conditioning circuitry), a
324:
315:
3629:A list of secure aggregation proposals for WSN
2988:Mitchell, Robert; Chen, Ing-Ray (2014-04-01).
2769:
954:This is a form of in-network processing where
272:
198:
3649:
3461:
2534:
2183:"ReVibe Energy – Powering The Industrial IoT"
1732:
895:
525:(usually radio transceivers or alternatively
3411:: CS1 maint: multiple names: authors list (
2987:
2828:
2535:Lyakhov, P. A.; Kalita, D. I. (2023-05-03).
2245:TENCON 2009 - 2009 IEEE Region 10 Conference
1635:
1320:
1161:
289:
3663:
3356:
3354:
3026:
2354:IEEE Transactions on Industrial Electronics
1296:Sohraby, K.; Minoli, D.; Znati, T. (2007).
839:Sensor data calibration and fault tolerance
809:was originally based on social simulation.
572:One major challenge in a WSN is to produce
374:An important factor in WATS development is
260:
3656:
3642:
3457:
3455:
1959:"U.S./Russian National Security Interests"
949:
432:The main characteristics of a WSN include
30:"WSN" redirects here. For other uses, see
3580:
3443:
3370:
3334:
3324:
3259:
3212:
3089:
3044:
2849:
2805:
2795:
2726:
2590:. Paris, France: IEEE. pp. 658–666.
2288:
2286:
2284:
2282:
2280:
2156:
2125:
2115:
2027:
2001:
1746:
1638:Networked Sensing Information and Control
1612:
1602:
1528:
1455:
1445:
1427:
1300:. John Wiley and Sons. pp. 203–209.
1205:
1187:
1103:
1085:
1059:
206:
173:
3984:Ad hoc On-Demand Distance Vector Routing
3432:Future Computing and Informatics Journal
3351:
2498:. Erode, India: IEEE. pp. 993–997.
940:
284:
234:
77:or connection to an external antenna, a
3619:IEEE 802.15.4 Standardization Committee
3452:
3425:
3033:Discrete Dynamics in Nature and Society
2770:Silva, D.; Ghanem, M.; Guo, Y. (2012).
2541:Automatic Control and Computer Sciences
1983:
1892:"Striving for a Safer World Since 1945"
14:
4040:
3581:Bulusu, Nirupama; Jha, Sanjay (2005).
3511:
3470:
2581:
2393:Computers & Electrical Engineering
2277:
2193:from the original on 22 September 2017
2089:
2050:
1922:
1920:
1918:
1916:
1886:
1884:
1351:
396:
354:Lawrence Livermore National Laboratory
247:
3637:
3245:
2822:
2702:
1410:Bilal, Muhammad; et al. (2017).
1390:10.4108/ICST.PERVASIVEHEALTH2009.5987
1329:Springer Science & Business Media
190:
2582:Shi, Junyang; Sha, Mo (2019-06-17).
2298:Fundamentals of Mobile Data Networks
1709:
1509:Environmental Science and Technology
1271:Dargie, W.; Poellabauer, C. (2010).
835:including AHLoS, APS, and Stardust.
796:retrieval of large volumes of data.
673:
664:
621:connectivity. With the emergence of
443:Ability to cope with node failures (
2829:Niazi, Muaz; Hussain, Amir (2011).
2150:
1913:
1881:
1735:ACM Transactions on Sensor Networks
1321:Oliveira, Joao; Goes, João (2012).
1129:ACM Transactions on Sensor Networks
991:Center for Embedded Network Sensing
847:
347:
24:
3556:
2223:from the original on 13 April 2018
1583:Atmospheric Measurement Techniques
1245:
905:Sensor nodes are prone to failure,
714:. TinyOS programs are composed of
427:
339:
160:
25:
4059:
3600:
3365:. Vol. 2. pp. 732–736.
2672:. Cairo: IEEE. pp. 313–320.
2405:10.1016/j.compeleceng.2016.02.015
1926:
815:
3606:
2733:
2504:10.1109/ICCMC56507.2023.10084135
2479:from the original on 2017-11-09.
2461:from the original on 2017-11-10.
2443:from the original on 2017-11-09.
2425:from the original on 2017-11-09.
1399:from the original on 2016-10-09.
996:List of ad hoc routing protocols
860:
405:
152:million remote units worldwide.
3419:
3300:
3239:
3188:
3147:
3106:
3061:
3020:
2981:
2936:
2897:
2763:
2745:
2661:
2620:
2575:
2528:
2483:
2465:
2447:
2429:
2411:
2380:
2345:
2318:
2235:
2205:
2175:
2083:
2057:IEEE Internet of Things Journal
2044:
1977:
1951:
1851:
1814:
1771:
1726:
1703:
1662:
1629:
1570:
1545:
1496:
1472:
1403:
1368:
1016:Optical wireless communications
1006:Mobile wireless sensor networks
923:Data integration and sensor web
820:
363:The data fusion process occurs
300:
3949:Sensor network query processor
3426:Rowayda, A. Sadek (May 2018).
1345:
1314:
1289:
1264:
1239:
1222:
1155:
1120:
1053:
1001:Meteorological instrumentation
961:secure data aggregation in WSN
908:For better collection of data,
653:Robustness and fault tolerance
383:U.S. House of Representatives'
155:
13:
1:
2678:10.1109/IntelCIS.2015.7397240
1965:. US House of Representatives
1046:
799:
3326:10.1016/j.inffus.2016.04.007
3006:10.1016/j.comcom.2014.01.012
2910:IEEE Personal Communications
2596:10.1109/INFOCOM.2019.8737467
919:but also on its neighbors'.
556:
466:to large scale of deployment
331:Structural health monitoring
325:Structural health monitoring
316:Water/waste water monitoring
225:dangerous gases for citizens
7:
3381:10.1109/icsens.2003.1279038
3082:10.1016/j.adhoc.2015.07.013
2339:10.1016/j.adhoc.2013.10.006
2253:10.1109/TENCON.2009.5395945
2020:10.1109/ACCESS.2020.2987483
1646:10.1007/978-0-387-68845-9_1
974:
869:
640:
603:
561:
273:Natural disaster prevention
199:Environmental/Earth sensing
10:
4064:
3445:10.1016/j.fcij.2018.02.003
2302:Cambridge University Press
935:Open Geospatial Consortium
926:
896:Distributed sensor network
661:receiver when not in use.
565:
409:
328:
304:
29:
3999:
3972:
3959:Wireless powerline sensor
3929:
3896:
3863:
3838:
3729:
3671:
3278:10.1007/s00500-013-1091-x
2868:10.1109/jsen.2010.2068044
2553:10.3103/S0146411623020062
2069:10.1109/JIOT.2019.2946971
1800:10.1109/JSEN.2014.2308725
986:Bluetooth mesh networking
381:WATS was profiled to the
290:Machine health monitoring
170:of gas or oil pipelines.
109:. Propagation can employ
3782:Near-field communication
3613:Wireless sensor networks
2728:10.1177/1550147718767605
2366:10.1109/TIE.2013.2267694
2157:Liz Young (2022-06-08).
1984:Aguilar, Mónica (2020).
1604:10.5194/amt-11-4605-2018
1362:10.1117/2.1201312.005120
1041:Wireless ad hoc networks
1031:Unattended ground sensor
708:event-driven programming
476:Cross-layer optimization
261:Water quality monitoring
49:wireless ad hoc networks
38:Wireless sensor networks
4048:Wireless sensor network
3665:Wireless sensor network
2994:Computer Communications
2721:(4): 1550147718767605.
2637:10.1145/2801948.2801999
2051:Pastor, Adolfo (2020).
1757:10.1145/1210669.1210670
1679:10.1145/2737095.2737113
1530:10.1021/acs.est.7b00891
1141:10.1145/1993042.1993049
950:Secure data aggregation
751:RIOT (operating system)
424:in various industries.
3990:Dynamic Source Routing
2090:Lloret, Jaime (2009).
1835:10.1109/HICSS.2009.313
1036:Virtual sensor network
768:programming language.
457:Heterogeneity of nodes
207:Air quality monitoring
174:Health care monitoring
3487:10.1145/958491.958521
3205:10.1109/ICDMW.2014.79
3164:10.1109/ICDMW.2013.74
1492:on November 23, 2015.
941:In-network processing
807:Agent-based modelling
418:low-power electronics
285:Industrial monitoring
235:Forest fire detection
107:wireless mesh network
47:These are similar to
3761:Bluetooth Low Energy
3615:at Wikimedia Commons
3577:," November 4, 2001.
3522:. pp. 196–201.
3481:. pp. 255–265.
3199:. pp. 525–532.
3158:. pp. 319–326.
2951:. pp. 612–621.
2838:IEEE Sensors Journal
2631:. pp. 255–260.
1929:"Sensing for Danger"
1780:IEEE Sensors Journal
1720:10.1117/2.3201305.05
1673:. pp. 274–285.
783:Wikisensing platform
764:and support for the
523:communication device
460:Homogeneity of nodes
32:WSN (disambiguation)
3944:Location estimation
3528:10.1109/MDM.2012.49
3270:2018arXiv181002679I
3046:10.1155/2015/683701
2957:10.1109/DSN.2005.58
2860:2011ISenJ..11..404N
2788:2012Senso..1213295S
2163:Wall Street Journal
2108:2009Senso...9.8722L
2012:2020IEEEA...872435I
1792:2014ISenJ..14.2232S
1595:2018AMT....11.4605F
1521:2017EnST...51.6999A
1438:2017Senso..17..979B
1180:2007Senso...7.2157X
1078:2020Senso..20.3113U
533:modules, secondary
397:Incident monitoring
369:Bayesian statistics
248:Landslide detection
3313:Information Fusion
3123:10.1109/SMC.2013.9
2797:10.3390/s121013295
1963:commdocs.house.gov
788:2021-06-09 at the
656:Self-configuration
650:Increased lifespan
646:following issues:
623:Internet of Things
586:local area network
507:quality of service
376:ease of deployment
191:Habitat monitoring
126:telecommunications
4035:
4034:
3611:Media related to
3592:978-1-58053-867-1
3537:978-1-4673-1796-2
3496:978-1-58113-707-1
3390:978-0-7803-8133-9
3254:(12): 2257–2277.
3224:978-1-4799-4274-9
3173:978-1-4799-3142-2
3132:978-1-4799-0652-9
3117:. pp. 7–13.
2922:10.1109/98.878533
2782:(10): 13295–332.
2687:978-1-5090-1949-6
2646:978-1-4503-3551-5
2605:978-1-7281-0515-4
2513:978-1-6654-6408-6
2437:"Wi-Sun Alliance"
2311:978-1-107-14321-0
2262:978-1-4244-4546-2
2117:10.3390/s91108722
2102:(11): 8722–8747.
1844:978-0-7695-3450-3
1688:978-1-4503-3475-4
1655:978-0-387-68843-5
1640:. pp. 9–37.
1515:(12): 6999–7008.
1447:10.3390/s17050979
1338:978-1-4614-1670-8
1307:978-0-471-74300-2
1282:978-0-470-99765-9
1246:Global, I. G. I.
1174:(10): 2157–2173.
1087:10.3390/s20113113
981:Autonomous system
881:computer networks
777:Examples include
710:model instead of
679:Operating systems
674:Operating systems
665:Routing protocols
590:wide area network
531:energy harvesting
503:energy efficiency
438:energy harvesting
279:natural disasters
91:energy harvesting
73:with an internal
16:(Redirected from
4055:
3939:Key distribution
3688:ERIKA Enterprise
3658:
3651:
3644:
3635:
3634:
3610:
3596:
3585:. Artech House.
3567:
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3018:
3017:
2985:
2979:
2978:
2940:
2934:
2933:
2901:
2895:
2894:
2892:
2886:. Archived from
2853:
2835:
2826:
2820:
2819:
2809:
2799:
2767:
2761:
2760:
2755:. Archived from
2749:
2743:
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2732:
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2706:
2700:
2699:
2665:
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2618:
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2532:
2526:
2525:
2487:
2481:
2480:
2473:"What is LTE-M?"
2469:
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2445:
2444:
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2415:
2409:
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2316:
2315:
2290:
2275:
2274:
2247:. pp. 1–6.
2239:
2233:
2232:
2230:
2228:
2209:
2203:
2202:
2200:
2198:
2187:revibeenergy.com
2179:
2173:
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2005:
1981:
1975:
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1924:
1911:
1910:
1908:
1907:
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1878:
1876:
1874:
1855:
1849:
1848:
1829:. pp. 1–7.
1818:
1812:
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1724:
1723:
1707:
1701:
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1627:
1626:
1616:
1606:
1589:(8): 4605–4615.
1574:
1568:
1567:
1565:
1563:
1553:"Breathe London"
1549:
1543:
1542:
1532:
1500:
1494:
1493:
1491:
1485:. Archived from
1484:
1476:
1470:
1469:
1459:
1449:
1431:
1407:
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1400:
1398:
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1189:10.3390/s7102157
1159:
1153:
1152:
1124:
1118:
1117:
1107:
1089:
1057:
890:local monitoring
848:Macroprogramming
683:embedded systems
348:Threat detection
151:
122:computer science
21:
4063:
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4054:
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3593:
3559:
3557:Further reading
3554:
3553:
3538:
3516:
3512:
3497:
3475:
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3424:
3420:
3404:
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3305:
3301:
3244:
3240:
3225:
3193:
3189:
3174:
3152:
3148:
3133:
3111:
3107:
3070:Ad Hoc Networks
3066:
3062:
3025:
3021:
2986:
2982:
2967:
2941:
2937:
2902:
2898:
2890:
2833:
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2707:
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2488:
2484:
2471:
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2453:
2452:
2448:
2435:
2434:
2430:
2419:"LoRa Alliance"
2417:
2416:
2412:
2385:
2381:
2350:
2346:
2327:Ad Hoc Networks
2323:
2319:
2312:
2291:
2278:
2263:
2240:
2236:
2226:
2224:
2211:
2210:
2206:
2196:
2194:
2181:
2180:
2176:
2167:
2165:
2155:
2151:
2088:
2084:
2049:
2045:
1996:: 72435–72460.
1982:
1978:
1968:
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1957:
1956:
1952:
1942:
1940:
1925:
1914:
1905:
1903:
1890:
1889:
1882:
1872:
1870:
1857:
1856:
1852:
1845:
1819:
1815:
1776:
1772:
1748:10.1.1.188.8180
1731:
1727:
1708:
1704:
1689:
1667:
1663:
1656:
1634:
1630:
1575:
1571:
1561:
1559:
1551:
1550:
1546:
1501:
1497:
1489:
1482:
1478:
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1396:
1381:
1373:
1369:
1350:
1346:
1339:
1319:
1315:
1308:
1294:
1290:
1283:
1269:
1265:
1256:
1254:
1244:
1240:
1232:
1228:
1227:
1223:
1160:
1156:
1125:
1121:
1058:
1054:
1049:
1021:Robotic mapping
977:
952:
943:
931:
925:
898:
872:
863:
850:
841:
823:
818:
802:
790:Wayback Machine
774:
735:, developed by
702:, developed by
676:
667:
643:
606:
570:
564:
559:
511:processing unit
430:
428:Characteristics
414:
408:
399:
350:
342:
340:Wine production
333:
327:
318:
309:
303:
292:
287:
275:
263:
250:
237:
209:
201:
193:
176:
163:
161:Area monitoring
158:
149:
102:to an advanced
79:microcontroller
35:
28:
23:
22:
18:Sensor networks
15:
12:
11:
5:
4061:
4051:
4050:
4033:
4032:
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4023:
4017:
4010:
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3827:
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3789:
3784:
3779:
3774:
3769:
3764:
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3748:
3743:
3737:
3735:
3731:Communications
3727:
3726:
3724:
3723:
3718:
3713:
3708:
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3695:
3690:
3685:
3679:
3677:
3669:
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3602:
3601:External links
3599:
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3571:
3568:
3558:
3555:
3552:
3551:
3536:
3510:
3495:
3469:
3451:
3438:(2): 166–177.
3418:
3389:
3350:
3299:
3248:Soft Computing
3238:
3223:
3187:
3172:
3146:
3131:
3105:
3060:
3019:
2980:
2965:
2935:
2896:
2893:on 2011-07-25.
2844:(2): 404–412.
2821:
2762:
2759:on 2017-11-11.
2744:
2701:
2686:
2660:
2645:
2619:
2604:
2574:
2547:(2): 154–166.
2527:
2512:
2482:
2464:
2446:
2439:. 2018-08-15.
2428:
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1628:
1569:
1557:Breathe London
1544:
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1306:
1288:
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1252:techxplore.com
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927:Main article:
924:
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913:
912:
909:
906:
897:
894:
871:
868:
862:
859:
849:
846:
840:
837:
832:Deborah Estrin
828:John Heidemann
822:
819:
817:
816:Other concepts
814:
801:
798:
773:
770:
716:event handlers
712:multithreading
675:
672:
666:
663:
658:
657:
654:
651:
642:
639:
635:NarrowBand IOT
605:
602:
566:Main article:
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305:Main article:
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3921:TinyDB-TOSSIM
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3746:IEEE 802.15.4
3744:
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3408:
3400:
3396:
3392:
3386:
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3378:
3373:
3372:10.1.1.1.6961
3368:
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3357:
3355:
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3342:
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3332:
3327:
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3318:
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3023:
3015:
3011:
3007:
3003:
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2995:
2991:
2984:
2976:
2972:
2968:
2966:0-7695-2282-3
2962:
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2258:
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2250:
2246:
2238:
2222:
2218:
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2192:
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2184:
2178:
2164:
2160:
2153:
2145:
2141:
2137:
2133:
2128:
2123:
2118:
2113:
2109:
2105:
2101:
2097:
2093:
2086:
2078:
2074:
2070:
2066:
2062:
2058:
2054:
2047:
2039:
2035:
2030:
2025:
2021:
2017:
2013:
2009:
2004:
1999:
1995:
1991:
1987:
1980:
1964:
1960:
1954:
1939:on 2 May 2017
1938:
1934:
1930:
1923:
1921:
1919:
1917:
1902:on 2016-03-16
1901:
1897:
1893:
1887:
1885:
1869:on 2 May 2017
1868:
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1854:
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1712:SPIE Newsroom
1706:
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1371:
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1359:
1355:
1354:SPIE Newsroom
1348:
1340:
1334:
1331:. p. 7.
1330:
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1309:
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1024:
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1009:
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1002:
999:
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936:
930:
920:
916:
910:
907:
904:
903:
902:
893:
891:
885:
882:
878:
867:
861:Reprogramming
858:
856:
845:
836:
833:
829:
813:
810:
808:
797:
793:
791:
787:
784:
780:
769:
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738:
734:
730:
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709:
705:
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697:
695:
691:
686:
684:
680:
671:
662:
655:
652:
649:
648:
647:
638:
636:
632:
629:is a form of
628:
624:
619:
615:
611:
601:
599:
595:
591:
587:
582:
579:
575:
569:
554:
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536:
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528:
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516:
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508:
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491:
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484:
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477:
474:
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468:
465:
462:
459:
456:
453:
449:
446:
442:
439:
435:
434:
433:
425:
423:
422:supply chains
419:
413:
406:Supply chains
403:
394:
392:
388:
384:
379:
377:
372:
370:
366:
361:
359:
358:"data fusion"
355:
345:
337:
332:
322:
313:
308:
298:
295:
282:
280:
270:
267:
266:Water quality
258:
255:
245:
242:
232:
230:
226:
222:
218:
214:
213:air pollution
204:
196:
188:
186:
185:sensing floor
182:
181:depth cameras
171:
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153:
147:
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105:
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84:
80:
76:
72:
69:
64:
62:
58:
54:
50:
45:
43:
39:
33:
19:
3931:Applications
3820:WirelessHART
3664:
3582:
3564:
3519:
3513:
3478:
3472:
3463:
3435:
3431:
3421:
3362:
3336:11572/196405
3316:
3312:
3302:
3251:
3247:
3241:
3214:10545/622629
3196:
3190:
3155:
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3108:
3091:11572/196409
3073:
3069:
3063:
3036:
3032:
3022:
2997:
2993:
2983:
2948:
2938:
2913:
2909:
2899:
2888:the original
2841:
2837:
2824:
2779:
2775:
2765:
2757:the original
2747:
2718:
2714:
2704:
2669:
2663:
2628:
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2544:
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2326:
2320:
2297:
2294:Guowang Miao
2244:
2237:
2225:. Retrieved
2216:
2207:
2195:. Retrieved
2186:
2177:
2166:. Retrieved
2152:
2099:
2095:
2085:
2060:
2056:
2046:
1993:
1989:
1979:
1967:. Retrieved
1962:
1953:
1941:. Retrieved
1937:the original
1933:str.llnl.gov
1932:
1927:Hills, Rob.
1904:. Retrieved
1900:the original
1895:
1871:. Retrieved
1867:the original
1863:str.llnl.gov
1862:
1853:
1826:
1816:
1783:
1779:
1773:
1738:
1734:
1728:
1711:
1705:
1670:
1664:
1637:
1631:
1586:
1582:
1572:
1560:. Retrieved
1556:
1547:
1512:
1508:
1498:
1487:the original
1474:
1419:
1415:
1405:
1377:
1370:
1353:
1347:
1323:
1316:
1297:
1291:
1272:
1266:
1255:. Retrieved
1251:
1241:
1224:
1171:
1167:
1157:
1132:
1128:
1122:
1072:(11): 3113.
1069:
1065:
1055:
1026:Smart object
965:
960:
956:sensor nodes
953:
944:
932:
917:
914:
899:
889:
886:
873:
864:
851:
842:
824:
821:Localization
811:
803:
794:
775:
755:
749:
745:Protothreads
737:Adam Dunkels
731:
725:
719:
715:
704:David Culler
698:
687:
677:
668:
659:
644:
607:
583:
577:
573:
571:
547:
522:
514:
510:
496:
480:
431:
415:
400:
380:
375:
373:
364:
362:
351:
343:
334:
319:
310:
307:Data logging
301:Data logging
296:
293:
276:
264:
251:
238:
221:particulates
210:
202:
194:
177:
164:
119:
100:star network
65:
46:
41:
37:
36:
4001:Conferences
3840:Programming
2399:: 576–590.
2360:(4): 1871.
2333:: 516–534.
2063:: 128–136.
2029:2117/328871
1990:IEEE Access
1969:26 February
1943:26 February
1873:26 February
568:sensor node
472:Ease of use
464:Scalability
387:Curt Weldon
168:geo-fencing
156:Application
95:sensor node
71:transceiver
53:temperature
3954:Sensor web
3772:ISA100.11a
3261:1810.02679
2851:1708.05875
2168:2022-07-08
2003:2312.07787
1906:2019-02-26
1786:(7): 1–8.
1429:1705.00764
1422:(5): 979.
1257:2023-02-09
1047:References
968:encryption
929:Sensor web
855:Sam Madden
800:Simulation
445:resilience
410:See also:
227:(e.g., in
217:pollutants
3976:protocols
3964:Telemetry
3878:Iris Mote
3842:languages
3756:Bluetooth
3733:protocols
3697:NanoQplus
3673:Operating
3407:cite book
3367:CiteSeerX
3345:1566-2535
3319:: 41–56.
3286:1433-7479
3100:1570-8705
3076:: 14–36.
3055:1026-0226
3014:0140-3664
2876:1893/3398
2569:258465232
2561:0146-4116
2522:257959382
2077:208111073
2038:218468946
1743:CiteSeerX
1198:1424-8220
1096:1424-8220
760:based on
557:Platforms
499:data rate
493:networks.
412:IoT Pixel
254:landslide
104:multi-hop
4042:Category
4028:(SenSys)
4006:journals
3911:LinuxMCE
3898:Software
3883:Sun SPOT
3865:Hardware
3802:Sidewalk
3763:(Wibree)
3399:15686293
3294:33273544
3233:14029568
3039:: 1–12.
3000:: 1–23.
2884:15367419
2816:23201997
2696:10688614
2614:86721016
2477:Archived
2459:Archived
2441:Archived
2423:Archived
2374:23562384
2271:30236796
2221:Archived
2191:Archived
2144:13104461
2136:22291533
1808:27135727
1741:: 1–es.
1697:15171166
1623:31595175
1562:27 April
1539:28578585
1466:28452937
1394:Archived
1216:28903220
1149:15576441
1135:: 1–31.
1114:32486411
975:See also
877:security
870:Security
786:Archived
781:and the
641:Software
604:Wireless
574:low cost
562:Hardware
486:network.
115:flooding
89:form of
87:embedded
61:pressure
3974:Routing
3873:Arduino
3855:LabVIEW
3811:TIBUMAC
3792:One-Net
3741:6LoWPAN
3721:OpenWSN
3706:OpenTag
3701:Nano-RK
3683:Contiki
3675:systems
3546:2990744
3266:Bibcode
3182:6460187
3141:6434158
2975:2018708
2856:Bibcode
2807:3545568
2784:Bibcode
2776:Sensors
2655:9188571
2127:3260610
2104:Bibcode
2096:Sensors
2008:Bibcode
1896:fas.org
1788:Bibcode
1765:7278286
1614:6781239
1591:Bibcode
1517:Bibcode
1457:5464775
1434:Bibcode
1416:Sensors
1235:. 2006.
1207:3864515
1176:Bibcode
1168:Sensors
1105:7309034
1074:Bibcode
1066:Sensors
1011:OpenWSN
762:Contiki
758:6LoWPAN
741:6LoWPAN
733:Contiki
551:routing
527:optical
515:sensors
391:Clinton
142:MobiCom
111:routing
83:battery
75:antenna
4022:(IPSN)
4016:(EWSN)
3986:(AODV)
3830:Z-Wave
3825:Zigbee
3807:Thread
3716:TinyOS
3693:LiteOS
3589:
3544:
3534:
3505:239370
3503:
3493:
3397:
3387:
3369:
3343:
3292:
3284:
3231:
3221:
3180:
3170:
3139:
3129:
3098:
3053:
3012:
2973:
2963:
2930:771769
2928:
2882:
2814:
2804:
2694:
2684:
2653:
2643:
2612:
2602:
2567:
2559:
2520:
2510:
2372:
2308:
2269:
2259:
2142:
2134:
2124:
2075:
2036:
1841:
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1763:
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1695:
1685:
1652:
1621:
1611:
1537:
1464:
1454:
1335:
1304:
1279:
1214:
1204:
1196:
1147:
1112:
1102:
1094:
779:Xively
727:LiteOS
700:TinyOS
618:Z-wave
614:Zigbee
610:Thread
594:server
539:RS-232
416:Using
365:within
229:London
150:
138:SenSys
85:or an
59:, and
3992:(DSR)
3916:OPNET
3797:OSIAN
3787:OCARI
3767:DASH7
3542:S2CID
3501:S2CID
3395:S2CID
3290:S2CID
3256:arXiv
3229:S2CID
3178:S2CID
3137:S2CID
2971:S2CID
2926:S2CID
2891:(PDF)
2880:S2CID
2846:arXiv
2834:(PDF)
2692:S2CID
2651:S2CID
2610:S2CID
2565:S2CID
2518:S2CID
2370:S2CID
2267:S2CID
2227:3 May
2197:3 May
2140:S2CID
2073:S2CID
2034:S2CID
1998:arXiv
1804:S2CID
1761:S2CID
1693:S2CID
1490:(PDF)
1483:(PDF)
1424:arXiv
1397:(PDF)
1382:(PDF)
1233:(PDF)
1145:S2CID
720:tasks
694:uC/OS
631:LPWAN
598:LPWAN
535:ASICs
452:MWSNs
68:radio
57:sound
3906:NS-2
3888:XBee
3815:TSMP
3777:MiWi
3711:RIOT
3587:ISBN
3532:ISBN
3491:ISBN
3413:link
3385:ISBN
3341:ISSN
3282:ISSN
3219:ISBN
3168:ISBN
3127:ISBN
3096:ISSN
3051:ISSN
3037:2015
3010:ISSN
2961:ISBN
2812:PMID
2682:ISBN
2641:ISBN
2600:ISBN
2557:ISSN
2508:ISBN
2306:ISBN
2257:ISBN
2229:2018
2199:2018
2132:PMID
1971:2019
1945:2019
1875:2019
1839:ISBN
1683:ISBN
1650:ISBN
1619:PMID
1564:2021
1535:PMID
1462:PMID
1333:ISBN
1302:ISBN
1277:ISBN
1212:PMID
1194:ISSN
1110:PMID
1092:ISSN
830:and
766:Java
743:and
718:and
690:eCos
627:LoRa
612:and
578:tiny
576:and
519:MEMS
241:fire
219:and
183:, a
146:EWSN
144:and
134:IPSN
124:and
93:. A
42:WSNs
3751:ANT
3524:doi
3483:doi
3440:doi
3377:doi
3331:hdl
3321:doi
3274:doi
3209:hdl
3201:doi
3160:doi
3119:doi
3086:hdl
3078:doi
3041:doi
3002:doi
2953:doi
2918:doi
2872:hdl
2864:doi
2802:PMC
2792:doi
2723:doi
2674:doi
2633:doi
2592:doi
2549:doi
2500:doi
2401:doi
2362:doi
2335:doi
2249:doi
2122:PMC
2112:doi
2065:doi
2024:hdl
2016:doi
1831:doi
1796:doi
1753:doi
1716:doi
1675:doi
1642:doi
1609:PMC
1599:doi
1525:doi
1452:PMC
1442:doi
1386:doi
1358:doi
1202:PMC
1184:doi
1137:doi
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