A large fraction of the old in our society live away from nears and dears. Newspapers of today are flooded with attacks towards them. These attacks are not only physical, they are technical too. This paper presents a system employing fraudulent message detection wiping out the chances of old beign victims of fraud SMS ,and face detection, home automation, health monitoring system ensuring their physical security. An android application and a blynk application installed in both old users andchild’s mobile are the two applications employeed. The fraudulentmessage detection module classifies SMS delivered to the oldusing SVM classifier. Spam SMS alerts are displayed in the android application. Face detection module uses ESP32Cam to capture video frames and thereafter OpenCV to crop faces anda face recognition model to classify obtained faces as known and unknown. Unknown face alerts are given via the android application. The old might be unable to turn ON/OFF lights and fans everytime. Home automation system uses two PIR sensors one for light and other for light. PIR sensors detect motion and pass signals to relay modules and accordingly fan and light turn ON and OFF. Lights and fans can also be operated manuallyvia the android application. Most importantly health is what that matters .A health monitoring system in the form of blynk application collects data from temparature and pulse sensors anddisplays in the application. Alerts are displayed once the vitals exceed the preset threshold value. Index Terms: SVM, Home Automation, Convolutional neural networks, OpenCV