ACM Transactions on Sensor Networks

The Internet of Things (IoT) has revolutionized the connectivity of diverse sensing devices, generating an enormous volume of data. However, applying machine learning algorithms to sensing devices presents substantial challenges due to resource ...

The digital transformation of factories has greatly increased the number of peripherals that need to connect to a network for sensing or control, resulting in a growing demand for a new network category known as the Equipment Area Network (EAN). The EAN ...

Acoustic communication has become a research focus without requiring extra hardware and facilitates numerous near-field applications such as mobile payment. To communicate, existing researchers use either an audible frequency band or an inaudible one. The ...

The widespread deployment of unattended LoRa networks poses a growing need to perform Firmware Updates Over-The-Air (FUOTA). However, the FUOTA specifications dedicated by LoRa Alliance fall short of several deficiencies with respect to energy efficiency, ...

Application-layer distributed denial-of-service (DDoS) attacks incapacitate systems by using up their resources, causing service interruptions, financial losses, and more. Consequently, advanced deep-learning techniques are used to detect and mitigate ...

The rising demand for utilizing fine-grained data in deep-learning (DL) based intelligent systems presents challenges for the collection and transmission abilities of real-world devices. Deep compressive sensing, which employs deep learning algorithms to ...

Drones represent a significant technological shift at the convergence of on-demand cyber-physical systems and edge intelligence. However, realizing their full potential necessitates managing the limited energy resources carefully. Prior work looks at ...

Unmanned Aerial Vehicles (UAVs) have gained increasing attention by both academic and industrial communities, due to their flexible deployment and efficient line-of-sight communication. Recently, UAVs equipped with base stations have been envisioned as a ...

Today, In-Vehicle Wireless Sensor Networks (IVWSNs) are being used by car manufacturers because it saves time in the assembling process; saves costs in the harness and after-sales; and makes vehicles lighter, which helps lessen fuel consumption. There is ...

Optical wireless communication (OWC) shows great potential due to its broad spectrum and the exceptional intensity switching speed of LEDs. Under poor conditions, most OWC systems switch from complex and more error prone high-order modulation schemes to ...

The increasing prevalence of smart devices spurs the development of emerging indoor localization technologies for supporting diverse personalized applications at home. Given marked drawbacks of popular chirp signal-based approaches, we aim at developing a ...

Android system has been widely deployed in energy-constrained IoT devices for many practical applications, such as smart phone, smart home, healthcare, fitness, and beacons. However, Android users oftentimes suffer from app crashes, which directly disrupt ...

The study focuses on achieving full view coverage in a camera sensor network to effectively monitor moving objects from multiple perspectives. Three key issues are addressed: camera direction selection, location selection, and moving object monitoring. ...

This study introduces an innovative method aimed at reducing energy consumption in sensor networks by predicting sensor data, thereby extending the network’s operational lifespan. Our model, Temporal Graph Sensor Prediction (TG-SPRED), predicts readings ...

This article introduces LinkStream, a liquidity analysis system based on multiple video streams designed and implemented for oilfield. LinkStream combines a variety of technologies to solve several problems in computing power and network latency. First, ...

Communication presents a critical challenge for emerging intermittently powered batteryless sensors. Batteryless devices that operate entirely on harvested energy often experience frequent, unpredictable power outages and have trouble keeping time ...

LoRa is widely deploying in aquatic environments to support various Internet of Things applications. However, floating LoRa networks suffer from serious performance degradation due to the polarization loss caused by the swaying antenna. Existing methods ...

The use of drones for collecting information and detecting bugs in orchards covered by nets is a challenging problem. The nets help in reducing pest damage, but they also constrain the drone’s flight path, making it longer and more complex. To address ...

Mobile crowdsensing leverages the power of a vast group of participants to collect sensory data, thus presenting an economical solution for data collection. However, due to the variability among participants, the quality of sensory data varies ...

In recent years, the focus has been on enhancing user comfort in commercial buildings while cutting energy costs. Efforts have mainly centered on improving HVAC systems, the central control system. However, it’s evident that HVAC alone can’t ensure ...

Acoustic motion tracking is rapidly evolving with various applications. However, existing approaches still have some limitations. Tracking based on single-frequency continuous wave (CW) faces cumulative errors in tracking and limited accuracy in tracking ...

UWB (Ultra-wideband) has been shown to be a promising technology to provide accurate positioning for the Internet of Things. However, its performance significantly degrades in practice due to Non-Line-Of-Sight (NLOS) issues. Various approaches have ...

Spatial crowdsourcing leverages the widespread use of mobile devices to outsource tasks to a crowd of users based on their geographical location. Despite its growing popularity, current crowdsourcing systems often suffer from a lack of transparency, ...

In the past decades, explosive numbers of Internet of Things (IoT) devices (objects) have been connected to the Internet, which enable users to access, control, and monitor their surrounding phenomenons at anytime and anywhere. To provide seamless ...

The visual information processing technology based on deep learning can play many important yet assistant roles for unmanned aerial vehicles (UAV) navigation in complex environments. Traditional centralized architectures usually rely on a cloud server to ...