Related papers: SIDSense: Database-Free TV White Space Sensing for…
Video Analytics Software as a Service (VA SaaS) has been rapidly growing in recent years. VA SaaS is typically accessed by users using a lightweight client. Because the transmission bandwidth between the client and cloud is usually limited…
WiFi sensing based on channel state information (CSI) collected from commodity WiFi devices has shown great potential across a wide range of applications, including vital sign monitoring and indoor localization. Existing WiFi sensing…
Satellite Image Time Series (SITS) of the Earth's surface provide detailed land cover maps, with their quality in the spatial and temporal dimensions consistently improving. These image time series are integral for developing systems that…
Wireless Sensor Networks (WSNs) are extensively utilized in critical applications, including remote monitoring, target tracking, healthcare systems, industrial automation, and smart control in both residential and industrial settings. One…
Epilepsy is a prevalent neurological disorder that affects millions of individuals globally, and continuous monitoring coupled with automated seizure detection appears as a necessity for effective patient treatment. To enable long-term care…
We propose to employ a recently developed IoT-based wireless technology, so called low-power wide-area networks (LPWANs), to exploit their long range, low power, and inherent compatibility to cloud storage and computing. We create a…
In the last decade, the advancement of the Internet of Things (IoT) has caused unlicensed radio spectrum, especially the 2.4 GHz ISM band, to be immensely crowded with smart wireless devices that are used in a wide range of application…
The growing prevalence of Internet of Things (IoT) technologies has led to a rise in the popularity of intelligent vehicles that incorporate a range of sensors to monitor various aspects, such as driving speed, fuel usage, distance…
Sixth-generation (6G) communication systems are expected to support direct-to-device (D2D) connectivity, enabling standard user equipment (UE) to seamlessly transition to non-terrestrial network (NTN), particularly satellite communication…
Smart-home IoT systems rely on heterogeneous sensor networks whose correctness shapes application behavior and the physical environment. However, these low-cost, resource-constrained sensors are highly prone to failure under real-world…
Preserving security and confidentiality in wireless sensor networks (WSN) are crucial. Wireless sensor networks in comparison with wired networks are more substantially vulnerable to attacks and intrusions. In WSN, a third person can…
Reducing energy consumption is a pressing issue in low-power machine-type communication (MTC) networks. In this regard, the Wake-up Signal (WuS) technology, which aims to minimize the energy consumed by the radio interface of the…
We describe a new, low-cost system designed to provide multi-sensor remote condition monitoring of modern scientific laboratories, as well as to allow users to perform actions from remote locations in case of detection of specified events.…
We introduce ViDaS, a two-stream, fully convolutional Video, Depth-Aware Saliency network to address the problem of attention modeling ``in-the-wild", via saliency prediction in videos. Contrary to existing visual saliency approaches using…
The impact of extreme events across the globe is extraordinary which continues to handicap the advancement of the struggling developing societies and threatens most of the industrialized countries in the globe. Various fields of Information…
A database-assisted TV white space network can achieve the goal of green cognitive communication by effectively reducing the energy consumption in cognitive communications. The success of such a novel network relies on a proper business…
Reconfigurable intelligent surface (RIS) has received widespread attention owing to the superiority of changing the wireless propagation environment intelligently. Channel feedback is essential in frequency division duplex (FDD)…
Autonomous systems and smart-industry deployments increasingly split computation across near-sensor, edge, and cloud resources, where tight energy, latency, and reliability budgets demand run-time adaptivity. In practice, deciding what to…
Deep learning models deployed on edge devices frequently encounter resource variability, which arises from fluctuating energy levels, timing constraints, or prioritization of other critical tasks within the system. State-of-the-art machine…
The global water crisis necessitates affordable, accurate, and real-time water quality monitoring solutions. Traditional approaches relying on manual sampling or expensive commercial systems fail to address accessibility challenges in…