Relevant bibliographies by topics / Low power WSN node

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Low power WSN node'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Low power WSN node"

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Chen, De Hai, and Wei Feng Chao. "Low-Power WSN Measurement Node for Greenhouse." Applied Mechanics and Materials 391 (September 2013): 501–4. http://dx.doi.org/10.4028/www.scientific.net/amm.391.501.

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The component of the greenhouse wireless sensor network was introduced, as the same time, its working process was presented. The wireless measurement nodes were designed based on nRF9E5. The hardware and software of the actuator nodes were studied, and according to the wireless communication system characteristic designing the system of hardware and software. The system was also debugged and test run. To reduce energy consumption, low-power components and low-power wireless transmission model were utilized, and the node had two operating model: active model and standby model. The wireless meas
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Wong, Yan Chiew, Szi Hui Tan, Ranjit Singh Sarban Singh, Haoyu Zhang, A. R. Syafeeza, and N. A. Hamid. "Low power wake-up receiver based on ultrasound communication for wireless sensor network." Bulletin of Electrical Engineering and Informatics 9, no. 1 (2020): 21–29. http://dx.doi.org/10.11591/eei.v9i1.1654.

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Wireless sensor network (WSN) consists of base stations and sensors nodes to monitor physical and environmental conditions. Power consumption is a challenge in WSN due to activities of nodes. High power consumption is required for the main transceiver in WSN to receive communication requests all the time. Hence, a low power wake-up receiver is needed to minimize the power consumption of WSN. In this work, a low power wake-up receiver using ultrasound data communication is designed. Wake-up receiver is used to detect wake-up signal to activate a device in WSN. Functional block modelling of the
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Hung, Chung-Wen, Hao-Jun Zhang, Wen-Ting Hsu, and Yi-Da Zhuang. "A Low-Power WSN Protocol with ADR and TP Hybrid Control." Sensors 20, no. 20 (2020): 5767. http://dx.doi.org/10.3390/s20205767.

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Most Internet of Things (IoT) systems are based on the wireless sensor network (WSN) due to the reduction of the cable layout cost. However, the battery life of nodes is a key issue when the node is powered by a battery. A Low-Power WSN Protocol with ADR and TP Hybrid Control is proposed in this paper to improve battery life significantly. Besides, techniques including the Sub-1GHz star topology network with Time Division Multiple Access (TDMA), adaptive data rate (ADR), and transmission power control (TPC) are also used. The long-term testing results show that the nodes with the proposed algo
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Yan, Chiew Wong, Hui Tan Szi, Singh Sarban Singh Ranjit, Zhang Haoyu, R. Syafeeza A., and A. Hamid N. "Low power wake-up receiver based on ultrasound communication for wireless sensor network." Bulletin of Electrical Engineering and Informatics 9, no. 1 (2020): 21–29. https://doi.org/10.11591/eei.v9i1.1654.

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Wireless sensor network (WSN) consists of base stations and sensors nodes to monitor physical and environmental conditions. Power consumption is a challenge in WSN due to activities of nodes. High power consumption is required for the main transceiver in WSN to receive communication requests all the time. Hence, a low power wake-up receiver is needed to minimize the power consumption of WSN. In this work, a low power wake-up receiver using ultrasound data communication is designed. Wake-up receiver is used to detect wake-up signal to activate a device in WSN. Functional block modelling of the
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Shah, Dhara Narendra. "Review on Improving Network Topology Lifetime by Optimal Node Position Clustering." International Journal of Emerging Research in Management and Technology 6, no. 6 (2018): 224. http://dx.doi.org/10.23956/ijermt.v6i6.273.

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Wireless sensor network(WSN) is facing key challenges like extending network lifetime due to sensor nodes having limited power supplies. Extending WSN lifetime is complicated because nodes often experience differential power consumption. For example, nodes closer to the sink in a given routing topology transmit more data and thus consume power more rapidly than nodes farther from the sink. Inspired by the huddling behavior of emperor penguins where the penguins take turns on the cold extremities of a penguin “huddle”, we propose mobile node rotation, a new method for using low-cost mobile sens
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Lin, Yang, Zhi Qun Li, Chen Jian Wu, Meng Zhang, and Zeng Qi Wang. "Design of Low Voltage Low Power LPF for WSN Node." Advanced Materials Research 760-762 (September 2013): 54–59. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.54.

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A fourth-order low-pass continuous-time filter for a WSN transmitter is presented. The active RC filter was chosen for the high linearity, designed by using the leapfrog topology imitates the passive filter. The operation amplifier (op-amp) adopted by the filter is feed-forward operation amplifier, which could get the GBW as large as possible under the low power consumption. The cut-off frequency deviation due to the process corner, aging and temperature deviation is adjusted by an automatic frequency tuning circuit. The filter in a 0.18μm RF CMOS technology consumes 1mW from a 1V power supply
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Ren, Si Kui, and Zhi Qun Li. "Design of Low Voltage Low Power ADC for WSN Node." Advanced Materials Research 760-762 (September 2013): 561–66. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.561.

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This paper presents a low power low voltage 7bit 16MS/s SAR ADC (successive approximation register analog-to-digital converter) for the application of ZigBee receiver. The proposed 7-bit ADC is designed and simulated in 180nm RF CMOS technology. Post simulation results show that at 1.0-V supply and 16 MS/s, the ADC achieves a SNDR (signal-to-noise-and-distortion ratio) and SFDR (Spurious Free Dynamic Range) are 43.6dB, 57.4dB respectively. The total power dissipation is 228μW, and it occupies a chip area of 0.525 mm2. It results in a figure-of-merit (FOM) of 0.11pJ/step.
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Sunitha R. and Chandrika J. "Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks." International Journal of Digital Crime and Forensics 13, no. 5 (2021): 130–44. http://dx.doi.org/10.4018/ijdcf.20210901.oa8.

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The exponential growth of the internet of things and united applications have renewed the scholarly world to grow progressively proficient routing strategies. Quality of service (QoS) and reduced power consumption are the major requirements for effective data transmission. The larger part of the applications nowadays including internet of things (IoT) communication request power effective and QoS-driven WSN configuration. In this paper, an exceptionally strong and effective evolutionary computing allied WSN routing convention is designed for QoS and power effectiveness. The proposed routing co
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Kondratjevs, K., A. Zabasta, and V. Selmanovs-Pless. "Development of Solar Powered Feeding Scheme for Wireless Sensor Networks in low Solar Density Conditions / Bezvadu Sensoru Tīklu Elektroapgādes Sistēmas Izstrāde, Kas Izmanto Saules Paneļus Un Darbojas Pazeminātas Saules Radiācijas Apstākļos." Latvian Journal of Physics and Technical Sciences 52, no. 4 (2015): 43–56. http://dx.doi.org/10.1515/lpts-2015-0022.

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Abstract In the recent years, there has been significant research focus on the safety and reliability of data harvesting and optimal energy consuming by wireless sensor network nodes. If external electrical power fails, the node needs to be able to send notifications to the utility demanding the use of backup energy strategies. The authors of the research offer an approach that can help to use PV panels as an alternative power source for WSN nodes in particular irradiation conditions. Survey and testing of the main types of PV panels offered on the market in conditions closed to real ones, in
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Du, Xiaotong, Wei Zhang, and Dong Li. "A Real-Time and Low Power Working Method for Mobile WSN." Mathematical Problems in Engineering 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/840647.

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In many mobile wireless sensor network (WSN) applications, the low power problem is often ignored to maintain the real-time property of monitoring nodes. To solve the long-time working problems of mobile nodes and the whole WSN network, this paper provides a new working method. First, the real-time and consumption features are compared between the Random Mechanism (RM) and Time-Division Mechanism (TDM) through experiments. Secondly, a mobile Time-Division Mechanism based on subnet node ID is designed to reduce the power consumption on the premise of real-time requirements effectively. At the s
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Dissertations / Theses on the topic "Low power WSN node"

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Huang, An-Lun. "Security primitives for ultra-low power sensor nodes in wireless sensor networks." Diss., University of Pretoria, 2007. http://hdl.handle.net/2263/24343.

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The concept of wireless sensor network (WSN) is where tiny devices (sensor nodes), positioned fairly close to each other, are used for sensing and gathering data from its environment and exchange information through wireless connections between these nodes (e.g. sensor nodes distributed through out a bridge for monitoring the mechanical stress level of the bridge continuously). In order to easily deploy a relatively large quantity of sensor nodes, the sensor nodes are typically designed for low price and small size, thereby causing them to have very limited resources available (e.g. energy, pr
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Ragavan, Rengarajan. "Reconfigurable FSM for Ultra-Low Power Wireless Sensor Network Nodes." Thesis, Linköpings universitet, Elektroniska komponenter, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-100121.

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Wireless sensor networks (WSN) play an important role in today’s monitoring and controlsystems like environmental monitoring, military surveillance, industrial sensing and control, smarthome systems and tracking systems. As the application of WSN grows by leaps and bounds, there is anincreasing demand in placing a larger number of sensors and controllers to meet the requirements. Theincreased number of sensors necessitates flexibility in the functioning of nodes. Nodes in wirelesssensor networks should be capable of being dynamically reconfigured to perform various tasks is theneed of the hour
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Shuck, Timothy A. "In-Node, Low Power Vehicle Classification and Identification System." Thesis, California State University, Long Beach, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10978575.

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<p> Traffic in major metropolitan areas is only increasing, requiring transportation authorities to mitigate traffic congestion. Intelligent Transportation Systems (ITS) offer transportation authorities the data needed to accurately measure current traffic patterns and to make accurate predictions of future patterns. </p><p> The proposed system is a wireless sensor network (WSN) incorporating small embedded processing nodes equipped with anisotropic magneto resistive (AMR) sensors which detect the magnetic field of passing vehicles for vehicle classification and identification. Machine learn
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Zhou, Dao. "Ultra Low-Power Wireless Sensor Node for Structural Health Monitoring." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/31103.

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Structural Health Monitoring (SHM) is the technology of monitoring and assessing the condition of aerospace, civil, and mechanical infrastructures using a sensing system integrated into the structure. Among variety of SHM approaches, impedance-based method is efficient for local damage detection. This thesis focuses on system level concerns for impedance-based SHM. Two essential requirements are reached in the thesis: reduction of power consumption of wireless SHM sensor, and compensation of temperature dependency on impedance. The proposed design minimizes power by employing on-board signal p
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Aulery, Alexis. "Architecture of Ultra Low Power Node for Body Area Network." Thesis, Lorient, 2016. http://www.theses.fr/2016LORIS419/document.

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Le réseau de capteurs porté est une technologie d’avenir prometteuse à multiple domaines d’application allant du médical à l’interface homme machine. Le projet BoWI a pour ambition d’évaluer la possibilité d’élaborer un réseau de capteurs utilisable au quotidien dans un large spectre d’applications et ergonomiquement acceptable pour le grand public. Cela induit la nécessité de concevoir un nœud de réseau ultra basse consommation pour à la fois convenir à une utilisation prolongée et sans encombrement pour le porteur. La solution retenue est de concevoir un nœud capable de travailler avec une é
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Holby, Björn, and Carl-Fredrik Tengberg. "Low Power Current Sensing Node Powered by Harvested Stray Electric Field Energy." Thesis, Linköpings universitet, Elektroniska Kretsar och System, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-121520.

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In this thesis, the possibility of harvesting energy from a multicore power cableconnected to a power outlet is presented and evaluated. By surrounding a powercable with a conductive material connected to ground, it is shown that the dif-ference in potential between the power cable and the conductive material causesa capacitance which can charge a capacitor that in combination with an energymanagement circuit can be used to wirelessly transmit data with an interval de-pending on factors like the length of the surrounding material and the type ofcable it is placed around. In addition to this, a
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UL, HAQ ANWAAR, and HAROON MALIK. "Cooperative Diversity and Power Consumption in Multi-hop WSN : Effects of node energy on Single Frequency Networks." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-21564.

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At the present time, wireless sensor networks are becoming more and more  common and energy consumption is a key factor in the deployment and  maintenance of these networks. This thesis compares non-SFN multi-hop and  a single frequency network (SFN) or cooperative diversity algorithms with  respect to the energy consumed by the nodes. Since the nodes have limited  power capacity it is extremely important to have an efficient algorithm. In  addition, the behaviour of the network when SFN is employed must be  studied and advice offered with regards to improvements in order to achieve  preferent
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Cochran, Travis. "Ultra Low Power Wake-up Receiver with Unique Node Addressing for Wireless Sensor Nodes." Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/76909.

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Power consumption and battery life are of critical importance for medical implant devices. For this reason, devices for Wireless Body Area Network (WBAN) applications must consume very little power. To save power, it is desirable to turn off or put to sleep a device when not in use. However, a transceiver, which is the most power hungry block of a wireless sensor node, needs to listen for the incoming signal continuously. An alternative scheme, is to listen for the incoming signal at a predetermined internal, which saves power at the cost of increased latency. Another and more sophisticated sc
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Deo, Sonali. "Mesh Networking in Low Power Location Systems (Swarm)." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-204558.

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Today, Internet of Things (IoT) is the driving force in making operations and processes smart. Indoor localization is such an application of IoT that has proven the potential of location awareness in countless scenarios, from mines to industries to even people. nanotron Technologies GmbH, based in Berlin, is one of the pioneers in low power location systems. nanotron's embedded location platform delivers location-awareness for safety and productivity solutions across industrial and consumer markets. The platform consists of chips, modules and software that enable precise real-time positioning
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Marinkovic, Djordje [Verfasser]. "A New Power-Processing Circuit for an Ultra-Low-Power Autonomous Sensor Node Based on a Piezoelectric Generator / Djordje Marinkovic." Aachen : Shaker, 2012. http://d-nb.info/1069047155/34.

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Books on the topic "Low power WSN node"

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Lopelli, Emanuele, Johan van der Tang, and Arthur H. M. van Roermund. Architectures and Synthesizers for Ultra-low Power Fast Frequency-Hopping WSN Radios. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-0183-0.

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Lopelli, Emanuele. Architectures and Synthesizers for Ultra-low Power Fast Frequency-Hopping WSN Radios. Springer Science+Business Media B.V., 2011.

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Tang, Johan van der, Arthur H. M. van Roermund, and Emanuele Lopelli. Architectures and Synthesizers for Ultra-Low Power Fast Frequency-Hopping WSN Radios. Springer Netherlands, 2013.

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Tang, Johan van der, Emanuele Lopelli, and Arthur H. M. Roermund. Architectures and Synthesizers for Ultra-low Power Fast Frequency-Hopping WSN Radios. Springer, 2011.

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Book chapters on the topic "Low power WSN node"

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Fernández-Berni, Jorge, Ricardo Carmona-Galán, and Ángel Rodríguez-Vázquez. "Wi-FLIP: A Low-power Vision-enabled WSN Node." In Low-Power Smart Imagers for Vision-Enabled Sensor Networks. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-2392-8_6.

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Fernández-Berni, Jorge, Ricardo Carmona-Galán, and Ángel Rodríguez-Vázquez. "Vision-enabled WSN Nodes: State of the Art." In Low-Power Smart Imagers for Vision-Enabled Sensor Networks. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-2392-8_2.

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Turchan, Krzysztof, and Krzysztof Piotrowski. "A Framework to Support Creation of AI Applications for Low-Power WSN Nodes." In Digital Interaction and Machine Intelligence. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74728-2_7.

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Suhonen, Jukka, Mikko Kohvakka, Ville Kaseva, Timo D. Hämäläinen, and Marko Hännikäinen. "Low-power WSN Technology." In Low-Power Wireless Sensor Networks. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-2173-3_1.

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Karimullah, Shaik, D. Vishnuvardhan, K. Riyazuddin, K. Prathyusha, and K. Sonia. "Low Power Enhanced Leach Protocol to Extend WSN Lifespan." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7961-5_51.

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Jiang, Yu, Jin Wang, Lili He, Yuanbo Xu, and Hongtao Bai. "A Low Power Balanced Security Control Protocol of WSN." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60717-7_5.

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Rath, Arabinda, S. Q. Baig, Bisakha Biswal, and Gayatri Devi. "Secured Data Transmission in Low Power WSN with LoRA." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9967-2_39.

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Kianpisheh, Somayeh, and Nasrolah Moghadam Charkari. "Dynamic Power Management for Sensor Node in WSN Using Average Reward MDP." In Wireless Algorithms, Systems, and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03417-6_6.

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García, V. H., and N. Vega. "Low Power Sensor Node Applied to Domotic Using IoT." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03763-5_6.

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Patil, Vilabha S., Yashwant B. Mane, and Shraddha Deshpande. "FPGA Based Power Saving Technique for Sensor Node in Wireless Sensor Network (WSN)." In Computational Intelligence in Sensor Networks. Springer Berlin Heidelberg, 2018. http://dx.doi.org/10.1007/978-3-662-57277-1_16.

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Conference papers on the topic "Low power WSN node"

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Tong, Zhanpeng, Heng Xiao, Xuekun Jia, and Li Li. "Design of Low-Power Underwater Backscatter Sensor Node." In 2024 IEEE 24th International Conference on Communication Technology (ICCT). IEEE, 2024. https://doi.org/10.1109/icct62411.2024.10946317.

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Khan, Rashid Eqbal, and Jyoteesh Malhotra. "Effective Energy-Selection Method for Heterogeneous WSN with Differential Power Sources Dependent on Node Energy." In 2025 Fourth International Conference on Smart Technologies, Communication and Robotics (STCR). IEEE, 2025. https://doi.org/10.1109/stcr62650.2025.11020390.

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Fang, Zhen, Zhan Zhao, Huanhuan Zeng, et al. "Ultra-Low Power WSN Node with Integrated THP Sensor." In 2006 1st IEEE International Conference on Nano/Micro Engineered and Molecular Systems. IEEE, 2006. http://dx.doi.org/10.1109/nems.2006.334902.

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Pasha, M. A., S. Derrien, and O. Sentieys. "A novel approach for ultra low-power WSN node generation." In IET Irish Signals and Systems Conference (ISSC 2010). IET, 2010. http://dx.doi.org/10.1049/cp.2010.0513.

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Premachandra, N. G. P. R., and Sampath Edirisinghe. "Battery-Less Sensor Node Design with Solar Panels and LoRa for Wireless Sensor Networks." In 3rd SLIIT International Conference on Engineering and Technology. SLIIT, 2024. http://dx.doi.org/10.54389/ojhy9648.

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A wireless sensor network (WSN) is a network of sensors that detect physical changes and convert them into analog or digital signals. These sensors communicate with each other to monitor and collect data from a specific area. Applications of WSNs range from environmental monitoring to agriculture, industrial automation, etc. The current WSN nodes are powered by rechargeable batteries and designed for short distances. The problems faced with current WSNs are short-distance communication, battery replacement in large, deployed networks, and rechargeable batteries that take longer time periods to
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Huang, Jie. "Research and Design of Low Power Consumption of WSN Node in Agricultural Greenhouse." In 2017 7th International Conference on Education, Management, Computer and Society (EMCS 2017). Atlantis Press, 2017. http://dx.doi.org/10.2991/emcs-17.2017.106.

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Nanhao Zhu and I. O'Connor. "Energy Measurements and Evaluations on High Data Rate and Ultra Low Power WSN Node." In 2013 IEEE 10th International Conference on Networking, Sensing and Control (ICNSC 2013). IEEE, 2013. http://dx.doi.org/10.1109/icnsc.2013.6548742.

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Hodon, Michal, Michal Chovanec, Lukas Cechovic, et al. "Maximizing performance of low-power WSN node on the basis of event-driven-programming approach: Minimization of operational energy costs of WSN node control unit." In 2015 20th IEEE Symposium on Computers and Communication (ISCC). IEEE, 2015. http://dx.doi.org/10.1109/iscc.2015.7405517.

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Agieb, R., I. Adly, and R. Ragai. "Two nodes UWB low power asset localization in WSN." In 2013 International Conference on Computer Applications Technology (ICCAT 2013). IEEE, 2013. http://dx.doi.org/10.1109/iccat.2013.6522059.

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Luo, Zhiyong, Li Geng, Ping Wang, and Jing Jiang. "An Information-Upload Approach with Low Power Consumption for a RFID-WSN Smart Node System." In 2011 7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2011. http://dx.doi.org/10.1109/wicom.2011.6040565.

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