Telemetry data play a pivotal role in ensuring the success of spacecraft missions and safeguarding the integrity of spacecraft systems. Therefore, the timely detection and subsequent notification of any abnormal events related to the functionality of...
Lossless compression of telemetry data in satellites is essential due to the stringent limitations of bandwidth and onboard storage. Traditional methods based on information theory and entropy coding, such as Huffman and Arithmetic coding, exploit st...
Anomaly detection based on telemetry data is a major issue in satellite health monitoring which can identify unusual or unexpected events, helping to avoid serious accidents and ensure the safety and reliability of operations. In recent years, sparse...
To effectively detect and identify the anomaly data in massive satellite telemetry data sets, the novel detection and identification method based on the pseudo-period was proposed in this paper. First, the raw data were compressed by extracting the s...
People with special medical monitoring needs can, these days, be sent home and remotely monitored through the use of data logging medical sensors and a transmission base-station. While this can improve quality of life by allowing the patient to spend...
In the radio telemetry systems of spacecraft, various data compression methods are used for data processing. When using any compression methods, the data obtained as a result of compression is formed randomly, and transmission over radio communicatio...
The volume of telemetry data is gradually increasing, both because of the increasingly larger number of parameters involved, and the use of higher sampling frequencies. Efficient data compression schemes are therefore needed in space telemetry system...
Safety and stability are critical in manned space missions, requiring an environmental control and life support system (ECLSS) of spacecraft to operate reliably. This study analyzed the time-series characteristics of telemetry data, including total p...
One of the key functions of driver monitoring systems is the evaluation of the driver’s state, which is a key factor in improving driving safety. Currently, such systems heavily rely on the technology of deep learning, that in turn requires cor...
Unmanned aerial vehicles have become essential tools in a wide range of applications. As drone operations grow more complex, the accurate prediction of battery runtime and aerodynamic flight safety risks, particularly those caused by wind, becomes in...
This article explores how different modalities of presenting telemetry data can support strategy management during solar-powered electric vehicle racing. Student team members using augmented reality head-mounted displays (AR HMD) have reported signif...
When using the conventional two-coil inductive link for the simultaneous wireless power and data transmissions in implantable biomedical sensor devices, the strong power carrier could overwhelm the uplink data signal and even saturate the external up...
To treat retinal degenerative diseases, a transcorneal electrical stimulation-based system is proposed, which consists of an eye implant and an external component. The eye implant is wirelessly powered and controlled by the external component to gene...
Today, the use of UASs (unmanned aerial systems) is rapidly expanding across civil, military, and scientific applications. The deployment of drones in close proximity to urban areas is becoming increasingly common, particularly during missions conduc...
Benford’s law (BL) specifies the expected digit distributions of data in social sciences, such as demographic or financial data. We focused on the first-digit distribution and hypothesized that it would apply to data on locations of animals freely mo...
This paper deals with the study of multi-channel adaptive noise cancellation with a focus on its application in electromagnetic (EM) telemetry. We presented new variable step-size least mean square (LMS) techniques: regularized variable step-size LMS...
Water levels in rivers are measured by various devices installed mostly in remote locations along the rivers, and the collected data are then transmitted via telemetry systems to a data centre for further analysis and utilisation, including producing...
The rapid evolution of connected and autonomous vehicles has significantly increased the importance of automotive telemetry as a fundamental component of intelligent transportation systems. Modern vehicles continuously generate large volumes of opera...
The growth of the marine renewable energy sector requires the potential effects on marine wildlife to be considered carefully. For this purpose, utilization distributions derived from animal-borne biologging and telemetry data provide accurate inform...
Data telemetry is a critical element of successful unconventional well drilling operations, involving the transmission of information about the well-surrounding geology to the surface in real-time to serve as the basis for geosteering and well planni...
Variations in species distribution, population structure, and behavior can provide a portfolio effect that buffers populations against rapid environmental change. Although diversity has been identified as a goal for effective resource management and...
For satellite or aircraft networks, tracking, telemetry, and control (TT&C) and data transmission between different nodes are necessary. Traditional measurement mostly adopts the frequency division duplex (FDD) mode and uses a continuous measurem...
Reliable forecasting of satellite telemetry is critical for spacecraft health management and mission planning. However, conventional data-driven methods often struggle to effectively capture both the long-term dependencies and local dynamics inherent...
Telemetry data are the most important basis for ground operators to assess the status of satellites in orbit, and telemetry data-based anomaly detection has become a key tool to improve the reliability and safety of spacecrafts. Recent research on an...
In recent years, missions requiring payload telemetry data transmission to ground stations have increasingly demanded a higher bandwidth. Traditional ranging techniques for spacecraft position determination often use a dedicated spectrum, reducing th...
Currently, most oil and gas wells are drilled by continuously transmitting downhole measured information (directional and geological information) in real-time to the surface to monitor and steer the well along a pre-defined path. The intelligent dril...
The growing number of on-orbit spacecraft and the increasing volume of telemetry data have made intelligent anomaly detection in multi-channel telemetry essential for mission operations. Current spacecraft anomaly detection methods primarily rely on...
The Indus Basin Irrigation System (IBIS) lacks a system for measuring canal inflows, storages, and outflows that is trusted by all parties, transparent, and accessible. An earlier attempt for telemetering flows in the IBIS did not deliver. There is n...
This paper presents a multi-participant driving simulation framework designed to support traffic experiments involving the simultaneous collection of vehicle telemetry and cognitive data. The system integrates motion-enabled driving cockpits, high-fi...
A telemetry system for real-time monitoring of the motions, position, speed and course of a ship at sea is presented in this work. The system, conceived as a subsystem of a radar cross-section measurement unit, could also be used in other application...
Cloud storage continues to experience recurring provider-side breaches, raising concerns about the confidentiality and recoverability of user data. This study addresses this challenge by introducing an Artificial Intelligence (AI)-driven hybrid archi...
The combination of GPS-Telemetry and resource selection functions is widely used to analyze animal habitat selection. Rapid large-scale assessment of vegetation structure allows bridging the requirements of habitat selection studies on grain size and...
Anomalies frequently occur during the operation of spacecraft in orbit, and studying anomaly detection methods is crucial to ensure the normal operation of spacecraft. Due to the complexity of spacecraft structures, telemetry data possess characteris...
Unmanned aerial vehicles (UAVs) increasingly demand robust onboard diagnostic frameworks to ensure safe operation under irregular telemetry and mission-critical conditions. This paper presents a real-time fault detection framework for unmanned aerial...
NAND flash-based solid state drives (SSDs) are increasingly common in computers, but they present a problem for forensic data recovery. SSDs use controller logic, flash translation layers, error correction, wear leveling, TRIM, garbage collection, an...
This study proposes an integrated framework for photovoltaic (PV) anomaly diagnosis combining unmanned aerial vehicle (UAV) radiometric thermography and red–green–blue (RGB) imagery, supervisory control and data acquisition (SCADA) teleme...
This applied systems-integration study addresses the “Impedance Mismatch” inherent in multi-energy microgrids—namely, the conflict where disparate physical domains traditionally force the use of isolated or highly rigid Supervisory...
Digital twin platforms for smart cities must continuously receive different types of data from sensors, gateways, and services, but in real situations these data are heterogeneous in terms of indicator names, measurement units, time rules, and object...
This study presents the design, fabrication, and experimental validation of the Hermes reusable model rocket platform integrating additive manufacturing, onboard sensing, and telemetry capabilities for low-cost aerospace experimentation. The rocket w...
In recent years there have been significant developments in satellite transmitter technology to follow the rapid innovation of sensors on-board new satellites. The CCSDS 131.2-B-1 standard for telemetry downlink, released in 2012, is part of the next...
This paper presents data-driven modeling and a results analysis. Group method data handling (GMDH), multivariable regression (MVR), artificial neuron network (ANN), and new proposed GMDH-featured ANN machine learning algorithms were implemented to mo...
This study compares deep learning models for point-level anomaly detection in multichannel satellite telemetry data. Raw event-based telemetry was converted into segment-based multivariate time series without windowing or feature extraction, allowing...
A novel non-coherent, low-power, area-efficient binary phase-shift keying demodulator for wireless implantable biomedical microsystems is proposed. The received data and synchronized clock signal are detected using a delayed digitized format of the i...
The flight data of a fixed-wing Unmanned Aerial Vehicle (UAV) can be evaluated by its designers in order to analyze its performance, to validate the project criteria and to make new decisions based on the data analyses. In this paper, the authors pro...
Programmable data planes are increasingly essential for enabling In-band Network Telemetry (INT), fine-grained monitoring, and congestion-aware packet processing. Although the P4 language provides a high-level abstraction to describe such behaviors,...
As data center networks grow in scale and complexity, the active inband network telemetry (AINT) system collects a broader range of network status metrics to provide comprehensive visibility for AINT-related network applications, but it also leads to...
Telemetry systems are increasingly finding applications in agriculture for a variety of tasks. These systems assist farmers in optimizing farm processes. By leveraging these technologies, energy resources can be used more efficiently, leading to redu...
Real-time telemetry is essential for performance optimization and safety in motorcycle racing, yet commercial solutions remain proprietary, expensive, and poorly extensible. This paper presents the design, implementation, and experimental evaluation...
In data center networks, when facing challenges such as traffic volatility, low resource utilization, and the difficulty of a single traffic scheduling strategy to meet demands, it is necessary to introduce intelligent traffic scheduling mechanisms t...
Cybersecurity researchers and security analysts rely heavily on data to train and test network threat detection models, and to conduct post-breach forensic analyses. Comprehensive data-including network traces, host telemetry, and contextual informat...
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