Accurate Boundary Detection and Refinement for Continuous Objects in IoT Sensing Networks

Zhou, Zhangbing; Zhang, Yaqiang; Yi, Xuefang; Chen, Chao; Ping, Haodi

doi:10.1109/mcom.2018.1800314

Cited by 12 publications

(6 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several techniques such as multiple traveling salesman problems along with time constraints and the vehicle routing are used for optimizing the route of mobile nodes. This strategy repeats until the elimination of candidate nodes and proceeds unless no more refinement is possible further 26 . An intelligent framework is created with IoT‐assisted WSNs for the wildfire detection (WD).…”

Section: Literature Reviewmentioning

confidence: 99%

“…This strategy repeats until the elimination of candidate nodes and proceeds unless no more refinement is possible further. 26 An intelligent framework is created with IoT-assisted WSNs for the wildfire detection (WD). In this work, a sleep Scheduling-based Energy Optimization Framework (SEOF) is introduced, which operate in two phases.…”

Section: Continuous Object Monitoringmentioning

confidence: 99%

See 1 more Smart Citation

A review on evolving domains of Internet of Things: Architecture, applications, and technical challenges

Sharma,

Sangwan,

Singh

2023

Int J Communication

View full text Add to dashboard Cite

SummaryThe Internet of Things (IoT) is a system that includes smart items with different sensors, advanced technologies, analytics, cloud servers, and other wireless devices that integrate and work together to create an intelligent environment that benefits end users. With its wide spectrum of applications, IoT is revolutionizing both the current and future generations of the Internet. IoT systems can be employed for broad‐ranging real applications, such as agriculture, the environment, cities, healthcare, and the industrial sector. In this paper, we briefly discuss the three‐tier architectural view of IoT, its different communication technologies, and the smart sensors. Moreover, we study various application areas of IoT such as the environmental domain, healthcare, agriculture, smart cities, and industrial, commercial, and general aspects. A critical analysis is shown for the existing schemes and techniques related to this work. Further, this paper addresses the basic context, tools and evaluation approaches, future scope, and the advantages and disadvantages of the aforestated IoT applications. A comprehensive analysis is provided for each domain along with its fundamental parameters like the quality of service (QoS), network longevity, scalability, energy efficiency, accuracy, and cost. Finally, this study highlights the technical challenges and open research problems existing in different IoT applications.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Continuous Object Monitoringmentioning

confidence: 99%

A review on evolving domains of Internet of Things: Architecture, applications, and technical challenges

Sharma,

Sangwan,

Singh

2023

Int J Communication

View full text Add to dashboard Cite

show abstract

“…All of them can find the targets in WSNs but need to promote the accuracy of the object boundary. A large number of researchers, such as the authors of [10], have done a considerable amount of work based on these algorithms to improve the precise algorithm of the boundary area of continuous targets.…”

Section: Contribution and Solutionsmentioning

confidence: 99%

“…For instance, Z. Zhou et al proposed an iterative method to precisely achieve the target edge [10] by repeatedly updating the candidate nodes to boundary nodes.…”

Section: Introductionmentioning

confidence: 99%

A Convolution Location Method for Multi-Node Scheduling in Wireless Sensor Networks

Han

Shang²,

Pan

2022

Electronics

View full text Add to dashboard Cite

The localization of continuous objects and the scheduling of resources are challenging issues in wireless sensor networks (WSNs). Due to the irregular shape of the continuous target area and the sensor deployment in WSNs, the sensor data are always discrete and sparse, and most network resources are also limited by the node energy. To achieve faster detection and tracking of continuous objects, we propose a convolution-based continuous object localization algorithm (named CCOL). Moreover, we implement the idea of greedy and dynamic programming to design an energy-saving and efficient strategy model (named MSSM) to respond to emergencies caused by multiple continuous targets in most specific WSNs. The simulation experiments demonstrate that CCOL is superior to other localization algorithms in terms of time complexity and execution performance. Furthermore, the feasibility of the multinode scheduling strategy is verified by setting different mobile nodes to respond to the target area in certain green WSNs.

show abstract

“…Finally, the sensing data of the abnormal node is routed to the sink node through the shortest path. Since the network is in a normal state most of the time [17], adopting a sleep mechanism can greatly reduce network energy consumption. However, the activation of neighboring nodes generates a large amount of redundant information transmission and consumes network energy.…”

Section: A Boundary Detectionmentioning

confidence: 99%

Energy-Efficient Boundary Detection for Continuous Objects in Collaborative Edge Networks

Kang

Zhou

et al. 2021

IEEE Access

Self Cite

View full text Add to dashboard Cite

Along with a large and increasing number of resource-constrained and battery-powered smart things being deployed in networks, an energy-efficient mechanism for continuous object boundary detection is fundamental for prolonging the network lifetime. Most of the existing studies focus on how to improve the boundary accuracy of continuous objects while ignoring the energy consumption of smart things in edge networks, which may lead to some smart things being in an unusable state. To address this issue, we propose an Energy-efficient Continuous object boundary Detection Mechanism, namely ECDM. This mechanism consists of two stages: (i) an edge-collaboration monitoring mechanism, where only sensory data relevant to toxic gas are transmitted among multi-edge networks, thus minimizing the number of exchanged sensory data involved in the detection, and reducing the transmission energy consumption of smart things; and (ii) a gas diffusion model is used to predict the diffusion of toxic gases, such that suspicious edge networks can be located quickly and efficiently, further reducing the energy consumption of smart things transmitting anomalous sensory data. Experimental results show that the energy consumption of ECDM is reduced by 34.5% compared to the latest boundary detection method that introduces a gas diffusion model while maintaining detection accuracy.INDEX TERMS Boundary detection, energy efficiency, gas diffusion model, edge networks.

show abstract

Accurate Boundary Detection and Refinement for Continuous Objects in IoT Sensing Networks

Cited by 12 publications

References 11 publications

A review on evolving domains of Internet of Things: Architecture, applications, and technical challenges

A review on evolving domains of Internet of Things: Architecture, applications, and technical challenges

A Convolution Location Method for Multi-Node Scheduling in Wireless Sensor Networks

Energy-Efficient Boundary Detection for Continuous Objects in Collaborative Edge Networks

Contact Info

Product

Resources

About