Search Results for "sensor data"
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42 projects for "sensor data" with 1 filter applied:
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Adafruit Unified Sensor Driver
Common sensor library
Many small embedded systems exist to collect data from sensors, analyze the data, and either take appropriate action or send that sensor data to another system for processing. One of the many challenges of embedded systems design is the fact that parts you used today may be out of production tomorrow, or system requirements may change and you may need to choose a different sensor down the road. -
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OpenPlanter
Language-model investigation agent with a terminal UI
OpenPlanter is an open-source Python project focused on building an intelligent automated planting or gardening system powered by software control and data processing. The repository is designed to help developers and hobbyists create programmable plant management workflows that can monitor, schedule, and optimize growing conditions. It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. The system is... -
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Open Wearables
Self-hosted platform to unify wearable health data
Open Wearables is an open-source initiative that aims to provide a community-driven ecosystem for wearable device software and interoperability by connecting sensor data, activity tracking, and health insights across multiple platforms and devices. Instead of relying on closed vendor ecosystems, the project provides standardized data models and APIs that let developers and hobbyists collect, sync, and analyze biometric and environmental data from wearables, DIY sensors, and open hardware projects. ... -
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Seamless Communication
Foundational Models for State-of-the-Art Speech and Text Translation
...The motivation is to move beyond “text in, text out” and enable direct, live, multi-turn exchange involving language, gesture, gaze, vision, and modality switching without user friction. The system architecture includes a real-time multimodal signal pipeline for audio, video, and sensor data, a dialog manager that can decide when to act (speak, gesture, point) or query, and a cross-modal reasoning layer that fuses perception with semantic context. The research prototype includes components for visual grounding (understanding when a user references something in view), gesture recognition and synthesis, and turn-taking mechanisms that mirror human conversational timing. ... -
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SLAM in Autonomous Driving Book
SLAM Technology in Autonomous Driving
SLAM in Autonomous Driving Book is the open-source code companion to the book SLAM in Autonomous Driving. It focuses on localization and mapping systems that combine LiDAR, IMU, GNSS, and vehicle motion data. The material begins with geometry, kinematics, Kalman filtering, inertial navigation, preintegration, and graph optimization. It then implements point-cloud processing, nearest-neighbor structures, ICP, NDT, scan matching, occupancy grids, and loop closure. Readers build both loosely... -
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PilottAI
Python framework for building scalable multi-agent systems
pilottai is an AI-based autonomous drone navigation system utilizing reinforcement learning for real-time decision-making. It is designed for simulating and training drones to fly safely through dynamic environments using AI-based controllers. -
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ESPectre
Motion detection system based on Wi-Fi spectre analysis (CSI)
ESPectre is an open-source motion detection system that transforms ordinary Wi-Fi signals into an ambient sensor capable of detecting movement without using cameras, microphones, or additional radio hardware, making it a privacy-preserving and cost-effective alternative for presence sensing and smart home automation. At its core, it analyzes Wi-Fi Channel State Information (CSI) — detailed measurements of how Wi-Fi waves change as they propagate — to mathematically detect disturbances caused by human movement between a Wi-Fi router and an ESP32 microcontroller, eliminating the need for machine learning or training data to operate effectively. ... -
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DriveLM
Driving with Graph Visual Question Answering
...The project introduces a new paradigm called graph visual question answering that structures reasoning about driving scenes through interconnected tasks such as perception, prediction, planning, and motion control. Instead of treating autonomous driving as a purely sensor-driven pipeline, DriveLM frames it as a reasoning problem where models answer structured questions about the environment to guide decision making. The system includes DriveLM-Data, a dataset built on driving environments such as nuScenes and CARLA, where human-written reasoning steps connect different layers of driving tasks. This design allows models to learn relationships between objects, behaviors, and navigation decisions through graph-structured logic. -
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FasterLIO
Faster-LIO: Lightweight Tightly Coupled Lidar-inertial Odometry
...It builds on FastLIO2 while replacing key spatial operations with parallel sparse incremental voxels. The design targets high update rates for both solid-state and spinning LiDAR sensors. It fuses LiDAR measurements with inertial data through an iterative Kalman-filter-based estimation pipeline. The software supports online ROS operation as well as offline processing of recorded bag files. Users can compile it with CMake or catkin, run it through Docker, visualize output in RViz, and save trajectories and point clouds. Configuration files support multiple sensor datasets, while selectable voxel implementations allow performance and stability tuning. -
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itom
itom - an Open Source Measurement, Automation and Evaluation Software
itom is an open source software suite for operating measurement systems, laboratory automation and data evaluation. One main application of itom is the development and operation of sensor and measurement system for instance in a laboratory environment. Therefore, the software has to be able to communicate with a wide range of different hardware systems, such as cameras or actuators and should provide a diversified and as complete as possible set of evaluation and data processing methods. ... -
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OSWorld
Benchmarking Multimodal Agents for Open-Ended Tasks
OSWorld is an open-source synthetic world environment designed for embodied AI research and multi-agent learning. It provides a richly simulated 3D world where multiple agents can interact, perform tasks, and learn complex behaviors. OSWorld emphasizes multi-modal interaction, enabling agents to process visual, auditory, and symbolic data for grounded learning in a simulated world. -
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CerberusCMS5
Cerberus Content Management System
Cerberus Content Management System is a dynamic, secure and infinitely expandable CMS designed after a Unix-Like model. It is a custom written Web Application Framework ( W.A.F. ) with a consistent and custom written Pre-Hyper-Text-Post-Processor Programming Code Framework ( P.C.F. ). This Web Application Software Project' aim is to be the fastest and most secure Web Application Framework, Web Application Programming Code Framework, Text, Voice and Video Communications Platform and Content... -
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Cerberus Content Management System 6
Cerberus Content Management System
Cerberus Content Management System is a dynamic, secure and infinitely expandable CMS designed after a Unix-Like model complete with a Unix-Like Kernel File named: Cerberus. It is a custom written Web Application Framework ( W.A.F. ) with a consistent and custom written Pre-Hyper-Text-Post-Processor Programming Code Framework ( P.C.F. ). This Web Application Software Project' aim is to be the fastest and most secure Web Application Framework, Web Application Programming Code Framework, Text,... -
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LSTMs for Human Activity Recognition
Human Activity Recognition example using TensorFlow on smartphone
...The repository includes data preprocessing scripts, neural network architecture definitions, and training pipelines that allow researchers to reproduce and modify the experiments. It serves as an educational example of how deep learning models can process temporal sensor signals for pattern recognition tasks. -
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Reskin Sensor Library
ReSkin Sensor Interfacing Library
Soft sensors have continued growing interest in robotics, due to their ability to enable both passive conformal contact from the material properties and active contact data from the sensor properties. However, the same properties of conformal contact result in faster deterioration of soft sensors and larger variations in their response characteristics over time and across samples, inhibiting their ability to be long-lasting and replaceable. ReSkin is a tactile soft sensor that leverages machine learning and magnetic sensing to offer a low-cost, diverse and compact solution for long-term use. ... -
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NaveGo
NaveGo: an open source MATLAB/GNU Octave toolbox for processing integr
NaveGo is an open source MATLAB/GNU Octave toolbox designed for processing integrated navigation systems, simulating inertial sensors and GNSS receivers, and profiling inertial sensors using methods like Allan variance—providing a community-driven simulation framework for navigation system design and analysis. I am reaching out to share an important update regarding the NaveGo project. Due to a shift in both my professional career and personal interests away from navigation systems, I have... -
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PS-Drone
Programming a Parrot AR.Drone 2.0 with Python - The Easy Way
The PS-Drone-API is a full featured SDK, written in and for Python, for Parrot's AR.Drone 2.0. It was designed to be easy to learn, but it offers the full set of the possibilities of the AR.Drone 2.0, including Sensor-Data (aka NavData), Configuration and full Video-support. The video function is not restricted to mere viewing, it is also possible to analyze video images data using OpenCV2. Obviously, the PS-Drone is perfect for teaching purposes; however, even the requirements for professional purposes can be satisfied. PS-Drone comes with a tutorial, explaining its most important commands and the drone's most important sensor values. ... -
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Kalibr Allan
IMU Allan standard deviation charts
...While manufacturers typically provide “white noise” values in IMU datasheets, the bias instability and random walk parameters must be determined experimentally. This project enables users to compute those values using Allan variance analysis from recorded IMU data. The workflow involves recording IMU measurements with the device stationary, converting ROS bag files into MATLAB-compatible formats, and then running MATLAB scripts to generate Allan deviation plots. These plots are analyzed to determine noise density and random walk parameters for both gyroscopes and accelerometers. The repository also includes example data and plots from real sensors such as the XSENS MTI-G-700, Tango Yellowstone Tablet, and ASL-ETH VI-Sensor, providing reference points for interpretation. -
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geog-server-embedded
GeoG Embedded Server
GeoG Embedded Server with GeoG's Own Database. -
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Attitude Estimator
A C++ implementation of a nonlinear 3D IMU fusion algorithm.
Attitude Estimator is a generic platform-independent C++ library that implements an IMU sensor fusion algorithm. Up to 3-axis gyroscope, accelerometer and magnetometer data can be processed into a full 3D quaternion orientation estimate, with the use of a nonlinear Passive Complementary Filter. The library is targeted at robotic applications, but is by no means limited to this. Features of the estimator include gyro bias estimation, transient quick learning, multiple estimation algorithms, tuneable estimator parameters, and near-global stability backed by theoretical analysis. ... -
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nmea4j
NMEA libary for java (protocol of GPS devices)
...First goal is a full implemenation of the NMEA 0183 protocol 3.0 (without proprietary extensions). The library provides parsers for NMEA sentences, gpsd-like network daemons and data generators for simulation and testing. This allows advanced sensor handling from cellphones/tablets/laptops with GPS up to vehicles/ships with NMEA sensors on board. -
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This project is a low cost & lowpower Datalogger based on BeagleBone Black. The data logger is an electronic device that records earthquakes(Sensor network), Wind ,daylight ,power used/produced on the street lamp over time. Data will then be uploaded via a wireless radio MESH network(868 Mhz) to a database server for later analyze. The Prototype is developed on two microcontrollers(AVR and ARM Cortex-A8) with the low power and
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NexusDataLink
Connect, monitor and control your (embedded) systems remotely. m2m/IoT
Connect, monitor and control your systems or embedded devices remotely (m2m/IoT) - for example your Raspberry Pi. The communication interface is defined in XML automatically providing a REST interface. NexusDataLink integrates smoothly in existing software or firmware and significantly reduces connection- or communication-related source code. -
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ar-drone
A node.js client for controlling Parrot AR Drone 2.0 quad-copters
...It provides a high-level API for common flight operations such as takeoff, landing, altitude changes, rotation, directional movement, and hovering. Programs can receive navigation telemetry including flight state, altitude, and other sensor data. Camera output can be accessed as raw video streams or converted into PNG frames through FFmpeg. The library also exposes predefined flight animations, LED sequences, configuration commands, and emergency recovery controls. An interactive REPL lets developers experiment with drone commands directly before building autonomous scripts. ... -
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fslurp
Fronius data tool for Linux
fslurp is a program to pull the data from a Fronius inverter systems via a serial port connection. It supports both single and multiple inverter systems through the Interface Card Easy and the Fronius Interface Card/DataLogger Box. Fronius Sensor Card devices are also supported. It supports both human-readable and delimited (CSV-style) text output. Sample output can be seen by building project and exercising one of the test simulator targets (e.g. simIFCEasy). ...
