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Intelligent Wireless Sensor Networks for IoT Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 987

Special Issue Editors

School of Computer and Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
Interests: Internet of things; RFID; wireless sensor networks; sensor node; communication systems
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Guest Editor
School of Internet of Things, Nanjing University of Posts and Telecommunications, Nanjing 210003, China
Interests: Internet of Things; edge intelligence and security

Special Issue Information

Dear Colleagues,

The Internet of Things (IoT) is the network where physical devices, sensors, appliances and other different objects can communicate with each other without the need for human intervention. Wireless Sensor Networks (WSNs) are main building blocks of the IoT. Both the IoT and WSNs have many critical and non-critical applications that touch almost every aspect of our modern life. Wireless sensor networks are providing a virtual layer in which information about the physical world can be accessed by any computational system. Thus, WSNs are considered a valuable asset for bringing the vision of IoT into reality. With the advancements in wireless technology and digital electronics, some tiny devices have started to be used in numerous areas in daily life. These devices are capable of sensing, computation and communicating. This Special Issue will focus on the recent prospective technologies, models, systems and applications in WSNs, IoTs, and advanced networking areas. The aim is to collect the most recent developments in Intelligent Wireless Sensor Networks for IoT Applications.

Topics of interest for this Special Issue include, but are not limited to:

  • Security and privacy issues in wireless sensor networks;
  • Applications of wireless sensor networks;
  • Energy efficiency of wireless sensors networks and IoT;
  • Deployment and optimization of WSNs in IoT.
  • Data collection, analysis, and visualization techniques for WSNs.

Dr. Jian Su
Dr. Siguang Chen
Guest Editors

Manuscript Submission Information

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Keywords

  • wireless sensor networks
  • Internet of Things
  • intelligent sensors

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Published Papers (2 papers)

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12 pages, 10533 KiB  
Article
IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions
by Christian Lang Rathke, Victor Costa de Andrade Pimentel, Pablo Javier Alsina, Caroline Cunha do Espírito Santo and André Felipe Oliveira de Azevedo Dantas
Sensors 2024, 24(17), 5799; https://doi.org/10.3390/s24175799 - 6 Sep 2024
Viewed by 370
Abstract
This study presents an IoT-based gait analysis system employing insole pressure sensors to assess gait kinetics. The system integrates piezoresistive sensors within a left foot insole, with data acquisition managed using an ESP32 board that communicates via Wi-Fi through an MQTT IoT framework. [...] Read more.
This study presents an IoT-based gait analysis system employing insole pressure sensors to assess gait kinetics. The system integrates piezoresistive sensors within a left foot insole, with data acquisition managed using an ESP32 board that communicates via Wi-Fi through an MQTT IoT framework. In this initial protocol study, we conducted a comparative analysis using the Zeno system, supported by PKMAS as the gold standard, to explore the correlation and agreement of data obtained from the insole system. Four volunteers (two males and two females, aged 24–28, without gait disorders) participated by walking along a 10 m Zeno system path, equipped with pressure sensors, while wearing the insole system. Vertical ground reaction force (vGRF) data were collected over four gait cycles. The preliminary results indicated a strong positive correlation (r = 0.87) between the insole and the reference system measurements. A Bland–Altman analysis further demonstrated a mean difference of approximately (0.011) between the two systems, suggesting a minimal yet significant bias. These findings suggest that piezoresistive sensors may offer a promising and cost-effective solution for gait disorder assessment and monitoring. However, operational factors such as high temperatures and sensor placement within the footwear can introduce noise or unwanted signal activation. The communication framework proved functional and reliable during this protocol, with plans for future expansion to multi-device applications. It is important to note that additional validation studies with larger sample sizes are required to confirm the system’s reliability and robustness for clinical and research applications. Full article
(This article belongs to the Special Issue Intelligent Wireless Sensor Networks for IoT Applications)
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24 pages, 594 KiB  
Article
Enhanced Harmonic Partitioned Scheduling of Periodic Real-Time Tasks Based on Slack Analysis
by Jiankang Ren, Jun Zhang, Xu Li, Wei Cao, Shengyu Li, Wenxin Chu and Chengzhang Song
Sensors 2024, 24(17), 5773; https://doi.org/10.3390/s24175773 - 5 Sep 2024
Viewed by 344
Abstract
The adoption of multiprocessor platforms is growing commonplace in Internet of Things (IoT) applications to handle large volumes of sensor data while maintaining real-time performance at a reasonable cost and with low power consumption. Partitioned scheduling is a competitive approach to ensure the [...] Read more.
The adoption of multiprocessor platforms is growing commonplace in Internet of Things (IoT) applications to handle large volumes of sensor data while maintaining real-time performance at a reasonable cost and with low power consumption. Partitioned scheduling is a competitive approach to ensure the temporal constraints of real-time sensor data processing tasks on multiprocessor platforms. However, the problem of partitioning real-time sensor data processing tasks to individual processors is strongly NP-hard, making it crucial to develop efficient partitioning heuristics to achieve high real-time performance. This paper presents an enhanced harmonic partitioned multiprocessor scheduling method for periodic real-time sensor data processing tasks to improve system utilization over the state of the art. Specifically, we introduce a general harmonic index to effectively quantify the harmonicity of a periodic real-time task set. This index is derived by analyzing the variance between the worst-case slack time and the best-case slack time for the lowest-priority task in the task set. Leveraging this harmonic index, we propose two efficient partitioned scheduling methods to optimize the system utilization via strategically allocating the workload among processors by leveraging the task harmonic relationship. Experiments with randomly synthesized task sets demonstrate that our methods significantly surpass existing approaches in terms of schedulability. Full article
(This article belongs to the Special Issue Intelligent Wireless Sensor Networks for IoT Applications)
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