This dataset accurately models the internal behavior of an IoT spectrum sensor (belonging to the ElectroSense platform and consisting of a Raspberry Pi 3 with a software-defined radio kit) when it is functioning normally and under attack. To accomplish it, the system calls of the IoT sensor are monitored under normal behavior, gathered, cleaned, and stored in a centralized directory. Then, the device is infected with current malware affecting IoT devices, such as the Bashlite botnet, Thetick backdoor, Bdvl rootkit, and a Ransomware proof of concept.

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This database includes subject-specific daily living activity data obtained from smartphones' inbuilt accelerometer, gyroscope, and linear acceleration sensors.

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This document has description of acoustic and vibration data of defect cases of centrifugal pump,  Test rig facility, sensor, and data acquisition device located at Precision Metrology Laboratory, Mechanical Engineering Department of Sant Longowal Institute of Engineering and Technology Longowal, India.  

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Our data set has 5136 records collected in 214 days. The sampling rate of the sensors is 1 hour. Each record includes the number of vehicles entering and leaving the parking lot in an hour, the CO2 concentration of every building floor at the recording time, and the power consumption of each floor in an hour.

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This dataset is gathered by using Inertial Measurement Unit Sensor (IMU) (MPU-9250) Positioned on the seat of Vehicle (like Bus, car bike, cycle). This Dataset is record with the help of IMU Sensor which gather only accelerometer data. Currently, collecting plain and rutty surface data through IMU Sensor by travelling in Bus, car, bike and cycle in different places in Haryana.

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This dataset complies 172 chipless RFID measurements that have been reported in the literature from 2005-2022. The dataset contain the year, reading distance, frequency range, tag type, reader setup, and reference for each entry.

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Vibration and Acoustic data for defect cases of the cylindrical roller bearing (NBC: NU205E) of Precision Metrology Laboratory, Mechanical Engineering Department, Sant Longowal Institute of Engineering and Technology, Longowal, India

This data can have the following applications:

-        Test the performance of various signal processing techniques.

-        Defect width measurement using vibration data

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 This dataset contains the data of three different positions of persons. The main focus of this dataset is on three positions those are Sit, Stand and Sleep. This dataset is collected by using a 3-axis accelerometer sensor value using the Inertial Measurement Unit (IMU) (MPU-9250) Sensor. We collected this data by positioning this instrument on the arm of the person.

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This dataset is gathered by using Inertial Measurement Unit Sensor (IMU) (MPU-9250) positioned on the seat of vehicle (Van). This dataset represents the real time sensory data collected with the help of vehicle i.e. School Van on a road at different places in Punjab. The objective of this dataset is to provide an accurate data for plain road and a road with pits.

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This dataset curbs real time sensory data collected through different vehicles such as Cycle, Car, Bike and Bus on the humpty-dumpty road. This dataset is collected by using Inertial Measurement Unit (IMU) sensor (MPU-9250) placed on the seats of vehicle. Through some vehicles (Cycle and Bike) are not having place to keep sensor, but it was designed to handle all the hurdles of road having potholes. The dataset aims to tell the exact accuracy of pothole and plane road. This dataset can be used in future for government to allocate budget to repair the rough road.

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