The vast majority of crashes are caused by the driver’s negligence about wearing seatbelts while using electronic devices while on the road where the health about drivers rests in the driver’s hands on the road. The aim of this article is to reduce the use of mobile devices while driving. This project was designed to ensure that the driver ties his seatbelts and also the mobile device is brought in silent mode before everything is determined for the drive. This can be done utilizing the Arduino controller which has been connected to the ESP8266 WiFi module, to detect the seat belt and the mobile Android service running in the back of the driver’s mobile device. Mobile mode is switched from active mode to silent mode once Wi-Fi is turned off.

Electrocardiogram (ECG) is an extremely powerful method for cardiovascular disease identification. Nevertheless, the ECG data is corrupted during the recording of ECG signals by several forms of noises as for example, power lines interference, base lines wandering, electrode movement, muscle movement (EMG) etc. Such noises / artifacts confuse the proper diagnosis of heart ailments and therefore their removal is much needed. Up to some degree traditional filters exclude the artifacts, but these filters are static and cannot adjust their coefficients to environmental change. Adaptive filtering algorithm and EMD are also utilized to exclude artifacts from the ECG signals. To decompose a signal whose IMFs represents the mean of a set of measurements, each consisting of a signal plus a white finite amplitudinal noise.

This article leads to the implementation and development of a Laboratory Virtual Instrument Engineering Workbench-based vital signs surveillance system for cardiovascular patients based on the Simple Mail Transfer Protocol technology. There are three main parts comprising the designed device, the first portion is a lap (circuit) built utilizing a hardware amplifier (AD620) called an electrocardiogram amplifier lap. Then comes the signal-conditioning lap with a practical amplifier (LM741). The second portion, is the signal conversion part from an analog signal to the digital signal using a data acquisition card. Moreover, cardiac data is processed and digital filtering techniques are performed to eliminate artifacts (noise) from the electrocardiogram signal acquired through the Laboratory Virtual Instrument Engineering Workbench system. Additionally, after preprocessing the cardiac signal the developed algorithm is utilized to calculate the heart-rate and analyze the heart condition (analyze the arrhythmia condition). In order to make the current labor more effective and attractive, Simple Mail Transfer Protocol technology has been added for remote diagnosis and monitoring purpose the state of the electrocardiogram signals easily over the internet, where the Simple Mail Transfer Protocol technology benefits is low-cost and effective in telediagnosis, which was previously a major problem overcome by this technique.