2,355 skills found · Page 6 of 79
SizheAn / MRIData repo for mRI: Multi-modal 3D Human Pose Estimation Dataset using mmWave, RGB-D, and Inertial Sensors
nebulastream / NebulastreamData management for the sensor-edge-cloud continuum
ssimunic / Temp MonitorInternet of Things data platform for temperature and humidity sensors with maps
SensorApps / Sensors2OSCAndroid app for sending sensor data via Open Sound Control (OSC).
denzilferreira / Aware ClientAWARE's Android client. This application allows researchers to easily collect sensor/plugin data locally or remotely to an AWARE server instance.
NekSfyris / ESEKF IMU GNSS LidarSensor fusion between IMU, GNSS and Lidar data using an Error State Extended Kalman Filter.
girishp92 / Human Activity Recognition Using Recurrent Neural Nets RNN LSTM And Tensorflow On SmartphonesThis was my Master's project where i was involved using a dataset from Wireless Sensor Data Mining Lab (WISDM) to build a machine learning model to predict basic human activities using a smartphone accelerometer, Using Tensorflow framework, recurrent neural nets and multiple stacks of Long-short-term memory units(LSTM) for building a deep network. After the model was trained, it was saved and exported to an android application and the predictions were made using the model and the interface to speak out the results using text-to-speech API.
mziccard / SecureitSample Android application that serves as a monitoring service by leveraging on device's accelerometer, camera and microphone. The app uses Wifi, mobile data, bluetooth or SMS to send notifications. Code is released open source to provide examples of how to exploit Android sensors and network capabilities.
Akajiaku11 / Forest Fire Alert Systemhis project implements a Forest Fire Detection and Alert System using sensor data (temperature, humidity, and smoke levels) to monitor forest fire risks.
deadskull7 / Human Activity Recognition With Neural Network Using Gyroscopic And Accelerometer VariablesThe VALIDATION ACCURACY is BEST on KAGGLE. Artificial Neural Network with a validation accuracy of 97.98 % and a precision of 95% was achieved from the data to learn (as a cellphone attached on the waist) to recognise the type of activity that the user is doing. The dataset's description goes like this: The sensor signals (accelerometer and gyroscope) were pre-processed by applying noise filters and then sampled in fixed-width sliding windows of 2.56 sec and 50% overlap (128 readings/window). The sensor acceleration signal, which has gravitational and body motion components, was separated using a Butterworth low-pass filter into body acceleration and gravity. The gravitational force is assumed to have only low frequency components, therefore a filter with 0.3 Hz cutoff frequency was used.
ittybittyapps / ARRecorderExample of using ARKit's private SPI to record and replay session sensor data
SteakEnthusiast / Akamai 2.0 Sensor Data Decryption ToolThis CLI tool allows you to convert the encrypted Akamai 2.0 sensor data payload back to its plaintext form.
JSLee121230 / Energy Ef Cient Data Collection In UAV Enabled Wireless Sensor NetworkEnergy Efficient Data Collection in UAV Enabled Wireless Sensor Network in matlab
ufoym / Mac AngleC++ library for reading MacBook lid angle sensor data
MattFryer / SmoothedAn Arduino library that allows smoothing of a sensor input using various methods. Uses a template class to ensure sensor readings in any numerical data type can be handled. This makes it both lightweight and flexible.
chenfeng-huang / Kaggle Silver Medal Solutioun CMI DBSDThis project uses wrist-worn sensor data—movement, temperature, and proximity—to distinguish body-focused repetitive behaviors (BFRBs) from everyday gestures. The goal is to build a model that improves BFRB-detection accuracy in wearable devices, supporting better mental health treatment.
elastic / MachinebeatThis is a beat for collecting data of machines, sensors and PLCs. At the moment this is supporting OPC UA and MQTT. More to add.
harshilpatel1799 / Iot Cyber Security With Machine Learning Research ProjectIoT networks have become an increasingly valuable target of malicious attacks due to the increased amount of valuable user data they contain. In response, network intrusion detection systems have been developed to detect suspicious network activity. UNSW-NB15 is an IoT-based network traffic data set with different categories for normal activities and malicious attack behaviors. UNSW-NB15 botnet datasets with IoT sensors' data are used to obtain results that show that the proposed features have the potential characteristics of identifying and classifying normal and malicious activity. Role of ML algorithms is for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets is possible. The ML model metrics using the UNSW-NB15 dataset revealed that ML techniques with flow identifiers can effectively and efficiently detect botnets’ attacks and their tracks.
ros-perception / Image Transport PluginsA set of plugins for publishing and subscribing to sensor_msgs/Image topics in representations other than raw pixel data.
ultralytics / KinectMATLAB computer vision project for 3D scene reconstruction from Microsoft Kinect depth-sensor data, with sample data and visualization workflows.
