Disclosed is a radar system that includes a plurality of slave radars, wherein each slave radar of the plurality of slave radars is configured to (i) broadcast a slave calibration signal within a predefined range (ii) receive a reflected version of the slave calibration signal, and (iii) to estimate slave intrusion localization information based on the reflected version of the slave calibration signal, and a master radar coupled to each slave radar of the plurality of slave radars, wherein the master radar is configured to, based on one or more calibration values, calibrate the one or more parameters.

A visible light smart home LiFi remote control system, comprising the following an information acquisition module for obtaining personnel information to output control signals with preset instructions. A LiFi transmitter, coupled with the information acquisition module, receives the transmission signal of the control signal with the output as the optical signal. A LiFi receiver, coupled with the LiFi transmitter, receives transmission signal compilation output control signal.

The present invention relates to an automated system for monitoring a plant tissue culture in a target area. The automated system includes a smart controller module equipped with preprogrammed software applications; a plurality of light tubes coupled to the smart controller module, wherein the each of the plurality of light tubes is composed of plurality of light emitting diodes; an air conditioning controller module communicably coupled to the smart controller module, configured to control the ambient temperature to be within a pre set temperature range by regulating the operation of an air conditioning system; one or more sensors communicably coupled to the smart controller module; a memory module coupled to the smart controller module; a remote control server communicably coupled to the smart controller module, configured to control remotely; and a remote control device communicably coupled to the smart controller module, configure to perform real time monitoring

The present invention provides a system for predicting heart arrhythmia comprising a heart rhythm acquisition means, wherein the heart rhythm acquisition means collects a heart rate signal; an output device, wherein the output device presents the output of a prediction; a machine learning prediction module, wherein the machine learning prediction module collects information describing variability in the heart rate signal over a specific period of a heart rate variability over a time segment, and determining relevance of the variability described in the collection to predict ventricular arrhythmia; and a cloud server, wherein the cloud server receives the heart rate signal and outputs the results via a network.

A radio frequency device design simulator system for optimizing output responses of radio frequency device, and more particularly to an antenna is provided herein. The radio frequency device design simulator system includes a screening module configured to apply a parametric screening to screen out at least one of a layout parameter from the output responses of the antenna, based on received a plurality of layout parameters.

Accordingly, embodiments herein disclose system and method for early detecting and analyzing the health of oil palm trees using IoT and stream data analytics classification based near-infrared spectrometer (NIRS). The present invention comprises an integrated near-infrared (NIR) spectrometer acquired spectral data from leaves and basal stem of oil palm seeding through a Raspberry Pi 3; a R-server and a cloud connector embedded in the Raspberry Pi 3 to connect the prototype of cloud for web-based configuration management. The R-server is established to enable access through a plurality of electronic devices to monitoring the analysis of the spectral data.

The present invention relates to the electrodes/sensors used in Electrocardiography (ECG) techniques used for tracing the electrical heart signals of a patient/user. The present invention provides a new type of electrode made up of cotton fabric. The cotton fabrics are uniquely stacked in a vertical manner.

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The various embodiments of the present invention provide an image of an insect is captured. The image is read for prediction of the insect species by converting the captured image into a grayscale. The captured image is further segmented into a plurality of images based on a number of insect in the captured image to derive interested features or points of interest in each image. Then, a pixel value of each point of interest is derived. An outline of the points of interest is drawn by using a convex hull algorithm which is further used to derive a surface area of an object (image of the insect) within the points of interest. The surface area data is fed in to a random forest model to calculate to a confidence score. The confidence score is used to predict the insect species.