相关论文: ZEL: Net-Zero-Energy Lifelogging System using Hete…

An accurate and reliable technique for predicting Remaining Useful Life (RUL) for battery cells proves helpful in battery-operated IoT devices, especially in remotely operated sensor nodes. Data-driven methods have proved to be the most…

Energy neutral operation of WSNs can be achieved by exploiting the idleness of the workload to bring the average power consumption of each node below the harvesting power available. This paper proposes a combination of state-of-the-art…

Artificial lighting is responsible for a large portion of total energy consumption and has great potential for energy saving. This paper designs an LED light control algorithm based on users' localization using multiple battery-less binary…

Machine learning and deep learning have shown great promise in mobile sensing applications, including Human Activity Recognition. However, the performance of such models in real-world settings largely depends on the availability of large…

The scale of scientific High Performance Computing (HPC) and High Throughput Computing (HTC) has increased significantly in recent years, and is becoming sensitive to total energy use and cost. Energy-efficiency has thus become an important…

Human motion detection is getting considerable attention in the field of Artificial Intelligence (AI) driven healthcare systems. Human motion can be used to provide remote healthcare solutions for vulnerable people by identifying particular…

This study examines stress levels in roadway workers utilizing AR-assisted multi-sensory warning systems under varying work intensities. A high-fidelity Virtual Reality environment was used to replicate real-world scenarios, allowing safe…

Energy-awareness for adapting task execution behavior can bring several benefits in terms of performance improvement in energy harvesting (EH) Internet of Things (IoT) devices. However, the energy measurement cost of acquiring energy…

A novel smart metering technique capable of anomaly detection was proposed for real-time home power management system. Smart meter data generated in real-time was obtained from 900 households of single apartments. To detect outliers and…

This paper considers energy-aware control for a computing system with two states: "active" and "idle." In the active state, the controller chooses to perform a single task using one of multiple task processing modes. The controller then…

The measurement of cosmic rays at energies exceeding 100 TeV per nucleon is crucial for enhancing the understanding of high-energy particle propagation and acceleration models in the Galaxy. HERD is a space-borne calorimetric experiment…

Physiological and behavioral data collected from wearable or mobile sensors have been used to estimate self-reported stress levels. Since the stress annotation usually relies on self-reports during the study, a limited amount of labeled…

Mental stress is a prevalent condition that can have negative impacts on one's health. Early detection and treatment are crucial for preventing related illnesses and maintaining overall wellness. This study presents a new method for…

Automatic sleep staging typically relies on gold-standard EEG setups, which are accurate but obtrusive and impractical for everyday use outside sleep laboratories. This limits applicability in real-world settings, such as home environments,…

In experiments searching for neutrinoless double-beta decay, the possibility of identifying the two emitted electrons is a powerful tool in rejecting background events and therefore improving the overall sensitivity of the experiment. In…

We propose SmartON, a batteryless system that learns to wake up proactively at the right moment in order to detect events of interest. It does so by adapting the duty cycle to match the distribution of event arrival times under the…

Healthcare is an important aspect of human life. Use of technologies in healthcare has increased manifolds after the pandemic. Internet of Things based systems and devices proposed in literature can help elders, children and adults…

Aiming for a greener transportation future, this study introduces an innovative control system for plug-in hybrid electric vehicles (PHEVs) that utilizes machine learning (ML) techniques to forecast energy usage in the pure electric mode of…

We introduce Perception Learning (PeL), a paradigm that optimizes an agent's sensory interface $f_\phi:\mathcal{X}\to\mathcal{Z}$ using task-agnostic signals, decoupled from downstream decision learning $g_\theta:\mathcal{Z}\to\mathcal{Y}$.…

This paper presents a novel system for monitoring cattle behavior and detecting estrus (heat) periods using sensor data and machine learning. We designed and deployed a low-cost Bluetooth-based neck collar equipped with accelerometer and…