Home Security using Facial Recognition

Smart home security and safety systems have gained more importance in recent years. This is attributable to their significant impact in reducing and preventing loss of assets and human life. The COVID-19 pandemic adds a new dimension to home security as potentially infected people or those not taking necessary precautions such as sanitization or wearing masks may enter homes and cause further transmission. The traditional security systems are effective in conventional scenarios but require human intervention and contact which can lead to the spread of the virus. This necessitates the development of smart security systems that are autonomous and contactless. This paper presents a novel IoT enabled home security system that restricts unauthorized access and at the same time ensures that permitted users are normothermic and are following proper COVID hygiene. The proposed system is a smart edge device that does not require a cloud platform for its computational needs. Facial recognition is used to authenticate and allow approved users to get access. If an unfamiliar person tries to enter the premises, the system takes a photo, computes mask detection on the image, measures temperature and sends these three data points as a WhatsApp notification to the administrative user. The door lock can then be controlled automatically or remotely using a WhatsApp bot.

Home automation system has achieved an enormous reputation in recent years, as day-to-day life is getting simpler due to the speedy growth of modern technology. Various implemented systems have been offered in the sphere of Home Automation but have apparently failed to provide cost-effective solutions for the same. In this paper, we provide a low-cost smart Home Automation and Security System (HASS) using Wireless Fidelity (Wi-Fi), and Bluetooth. These materialize the concept of internetworking of smart devices. A Wireless Sensor Network (WSN) based on Wi-Fi is considered to monitor and control the smart environment, safety as well as electrical parameters of a smart interconnected home. The Android application-based Graphical User Interface (GUI) on a Smartphone is used to give facility to users for seamless control over the devices in a smart home. It may also consist of home security for example access control and alarm systems. When connected to the Internet, home devices are an important element of the Internet of Things (IoT). Home security includes both the security hardware placed on a property and individuals' personal security practices. Security devices consist of a door locking, alert alarm, lighting, motion detectors, and security camera system. Additionally, several special features include such as ensuring windows are closed, each door is locked, all alarms are activated, and extra keys are not secret outside.

Internet of things and Automation systems have taken over the world at present times. Home security has always been a field of concern among mass people. Making home security systems safer, cheaper and easy to understand is a challenge that many engineers around the world are striving to achieve in developing countries. Considering the economic condition of people of a developing country like Bangladesh, we propose an IoT based smart home security and automation system named `Facebook messenger Chatbot' which is made using Raspberry PI as the central processor. It will enable its users to use it free of cost as Facebook messenger app is free in Bangladesh. People can use it from home or any remote location and can control digital home appliances like fans, lights etc. Smart door locking system, face recognition, gas leakage detection, temperature detection and control, humidity detection, fire detection, which has been done through collecting data from different sensors and passing them to Raspberry PI and then PI passes these to the BOT through a REST API, are the additional features that make our security system safer, effective and easier to use compared to other existing approaches.

The system is regarding the remotely overseen Door availability and voice alarming with the help of Smart Phone. It captures the guest picture at the Door as Email caution. Use of Smart home security control framework became essential in our day to day life. This paper describes the outline of an advanced home security framework. In this method the door availability has been controlled based on guest character by considering the human movement location and remotely checking innovation. This paper describes the remote control framework execution and organization and allows the validated individuals in to a home as it were. This Security Framework can be implemented by using switch/calling bell and a Camera module. The camera module captures the pictures of the guest separately and ideally to make the home security framework alive on demand. In this method we used an Electromagnetic entryway bolt module which created the entryway availability. This proposed framework deploys a controller interface framework and LPC 2148. If a guest press calling bell at the door then the web Camera module is interfaced with switch to capture pictures and send these pictures as Email caution with the help of TCP/IP protocol. Now, we can control this home security system by seeing camera module video stream with the help of Smart cell Phone. Like this, the proposed home security framework allows us for sending an order as a reply of voice ready whenever the gatecrasher recognized using smart phone. By using android stage and improved JavaScript, the Clients can see the guest on the screen and able to control the entryway by locking or unlocking the door. This software can be used in a wide range of application where the physical nearness can't be possible forever i. e in territories. The entire control framework is implemented with LPC 2148 now a days usage of smart lock system is increasing day by day in wide range of applications. This efficient effort less low power calling bell based home lock system is essential for security purpose in every home and offices. So many nations are worked on home based locking frame work to implement advanced technologies in it. Most of smart houses and business offices are associated with a chip for security purpose. Though numerous advancements take place, the clients face troubles i. e interface problems in utilizing this smart lock system. To avoid such type of issues i proposed microcontroller. This advanced home security system is useful for real time home environment.

This For high dimensional dataset processing Security has been becoming an important issue everywhere. Every individual wants his home, industry, bank secured. Home security is becoming necessary. Now days as the possibilities of theft are increasing day by day. Hardware of this system has been designed using microcontroller , IR (Passive Infra Red) motion sensor as the primary sensor for motion detection, a Wifi module ESP8266 to connect and communicate using the internet, keypad and buzzer for alarm. This Security System can monitor home space that is surrounded by IR sensor by sending SMS, and make people panic by turning on the buzzer when passing nearby area that detected by IR sensor. The Home Security System has been tested and can successfully detect human movement.Smart home safety and security systems have gained much importance over the last few years owing to their notable impact in reducing and preventing losses in resources and human life caused by unwanted situations that could occur while homeowners are far away from their homes.

With the increasing application of the Internet of Things (IoT) devices in home automation, the prospect for home security has become even more integral. While there have been many notable developments in the field of smart home security systems for the past decade, the possibilities to develop and employ a multitude of features for an IoT based security system keep growing. Our proposed design introduces a cheap IoT based home security system that enables the user to have complete control over the system remotely as well as get live video feedback over the internet by using our custom- designed android application. The android application utilizes a real-time database (Firebase) for interpreting the sensor data. The android application also provides other features such as – password management, activation or deactivation of the system and alert option. The security system combines a motion sensor and a camera module for intruder detection and alerts the user instantly through an online alert notification. For evidence purposes, snapshots of the intruder can be taken during live video monitoring from the android application. Additionally, a GSM module is used to send an SMS alert about the intruder over the cellular network.

This project presents a Home Automation Security System that integrates face detection and recognition with RFID technology using a Raspberry Pi. The system aims to enhance security and access control in homes by automating the process of user authentication through facial recognition and RFID tags. The system utilizes a Raspberry Pi as the central control unit, a camera module for face detection and recognition, and an RFID reader to scan RFID tags for additional access control. The system functions by scanning an RFID tag, and upon detection of a valid tag, it activates the camera to capture the face of the person requesting access. The captured image is then processed using OpenCV and face_recognition libraries in Python to match the face with a pre-stored database of authorized individuals. If both the RFID tag and face match the stored data, the system grants access by performing automation actions such as unlocking doors or turning on lights. Keywords- Raspberry Pi, Pi Camera, Face Detection, Face Recognition, RFID Technology, RFID Tag Verification.

A home security system is a need in today's world. However, the usage of keys, security cards, passwords or pattern locks to open most doors has recently been outlawed. Yet robbery and identity theft are much more dangerous repercussions of key loss than the actual loss of a key itself Consequently, this has been deemed a severe problem. A door access control system was successfully installed thanks to the usage of the Internet of Things (IoT). As well as serving as the primary controller for face recognition, youth system, and locking system, the Raspberry Pi is employed as a compact computer board that can be programmed. The guy standing in front of the entryway is captured by a camera on the wall. Whenever the system fails to recognise a person's face, a warning will be sent. Using the Internet of Things, a user may control who has access to a door (IoT). Facial recognition, Rasberry Pi, Internet of things (IOT), and home security systems are some of the terms we'll be using today.

The study outlines the design and implementation of a Home Security and Intrusion Detection System based on IoT with the goal of supplying homeowners with real-time monitoring, intelligent threat detection, and immediate alert systems. The suggested system will combine several Internet of Things (IoT) devices, including PIR and ultrasonic sensors, camera modules, and microcontrollers (Arduino/Raspberry Pi) and Wi-Fi modules to create a smart, autonomous, and connected surveillance network. The microcontroller processes data of the sensing layer and sends it via MQTT/HTTP protocols and displays on a mobile or web-based platform so that the user can immediately respond. To test the system in different scenarios of intrusion, a variety of intrusion conditions were applied to test the accuracy of detecting, the time of responding to alerts, and the power consumption of the system. The experimental results had shown a high success rate of detection of 98 % and low false alarms and low power consumption and the networks had constant connectivity. Evaluation on ease of set-up, accuracy, and reliability of the system was also done by the users who expressed more than 96 % satisfaction. Comprehensively, the study has served to advance smart home technologies due to the ability to offer an efficient, scalable, and affordable IoT-based security system that can protect in real-time and expand in the future through the inclusion of AI and cloud.

Current attendance methods, though simple, are prone to manipulation and can be time consuming for both educators and students. For instance, manual systems and QR code based methods allow students to register attendance on behalf of others due to the lack of unique identification. While calling names individually improves security, it disrupts the learning process by consuming significant time. This study addresses these issues by developing an autonomous robot, CObot, equipped with a facial recognition system powered by a Raspberry Pi microcontroller. CObot navigates classrooms autonomously, avoiding obstacles, and efficiently records attendance without requiring movement from students or educators. The use of facial recognition ensures that only registered individuals can mark attendance, creating a secure and tamper-proof system. Additionally, the integration of Internet of Things (IoT) technology enables real-time data transfer to Google Sheets, simplifying record-keeping and reducing educators administrative workload. A 3D-printed, customizable car structure enhances the robot design, while the Raspberry Pi 5 was selected over alternatives like the ESP32-S3 for its superior processing power and faster data transfer speeds, ensuring smoother operations. In testing with 60 participants, the Raspberry Pi 5 demonstrated a 99% accuracy rate in facial recognition, outperforming the ESP32-S3 90% accuracy. By saving time, improving security, and reducing manual effort, CObot enhances the classroom environment, benefiting both students and educators. While the improvement in attendance systems may appear incremental, CObot represents a meaningful step toward fostering a more efficient and effective learning environment.

As the number of patients treated in-home are increasing exponentially mainly in countries such as Japan, US A and Europe etc., these people often enter into a critical situation that may require help immediately (e.g. when facing an accident, or becoming depressed). Researches and Advances in computing areas and the Internet of Things (IOT) have provided efficient and cheap equipments including wireless communication and cameras, such as smart phones or embedded devices that enable the deployment of Health S mart Homes (HS H) that can provide medical treatment of patients in their homes. The images captured from these cameras can help nurses or caretakers of patients to provide timely help. The use of such patient images and emotional detection to assist patients and elderly people within home is provided in this article. Internet of Things and Cloud computing can work together, which can address to the Big Data problems. Big data is actually a term used for a huge data set that performs operations like storage of data, analysis, sharing, transfer, predictive analysis; updating etc. data set can grow rapidly. Data sets have different analytics on data that involve process of inspecting, transformation and modeling of data so as to discover new information, and to reach on some particular decision. There are some particular data analysis techniques from which data mining is a popular one which focuses on modeling and discovery of new facts. The discovered knowledge helps in predictive analysis purposes as well as text analysis. Further on data mining is performed on data set which involves discovery of patterns by applying different operations at databases, and using artificial intelligence, machine learning, statics etc. Keywords: Cloud computing, IOT, AI, face recognition, big data, data mining.

The objective of this research is to develop a home security system that utilizes facial recognition technology using the Haar Cascade method and ESP32CAM. In the face of criminal threats, the importance of an effective home security system is increasing. The facial recognition method employed in this study is the Haar Cascade method, which utilizes specific facial features to identify individual identities. The ESP32CAM sensor is used as a camera to capture facial images of the home occupants. The research involves the process of collecting facial image data from the home occupants, which is then used to train the facial recognition model. Subsequently, the model is implemented in a home security system that is connected to the internet and equipped with motion sensors. When motion is detected, the ESP32CAM camera captures an image of the visitor's face and compares it with the previously identified facial data. If a match is found, the system grants access to the visitor. The research results demonstrate that the developed home security system achieves accurate facial recognition with a high success rate. Therefore, this system has the potential to enhance home security and provide better protection for its occupants

This study is a qualitative study with a descriptive approach, namely describing each main object used in this study, including the Internet of Things, Smart Room Customization, and Service Quality. The data used in this study are secondary data that researchers obtain from various credible sources such as books, scientific articles, credible websites, and various other research sources. The data obtained are analyzed by stages of data collection, data reduction, and drawing conclusions. The result in this aticle show. the Internet of Things can create smart Room Customization. Smart Room Customization is built using the concept of the Internet of Things (IoT), a concept where an object has the ability to receive and send data over a network without requiring human interaction to a computer. The Internet of Things (IoT) is a concept that aims to expand the benefits of continuously connected internet connectivity. Kaur, Singh, Khairwal, & Jain conducted a study on the Home Automation and Security System with the GSM communication method and Android Application, the system can control equipment and help protect thieves because there is an alarm and can send signals to the owner using Android [. Giorgos Sfikas also conducted a study Creating a Smart Room using an IoT approach, a study that explains the concept of building a Smart Room using Arduino and a Bluetooth module to control electronic equipment. In the end, the benefits that the researcher mentioned above serve to facilitate customers in accessing, utilizing facilities, and other things that can facilitate customers to travel and stay in an integrated place and hotel. The convenience that the researcher mentioned above is one form of improving the quality of tourism services.

 Internet of Things (IoT)-enabled intelligent systems are proliferating rapidly, providing the capability to connect virtually any device to the Internet. Consequently, this concept can be effectively utilized in home security applications. In this paper, we have introduced an IoT-enabled system designed to send security alerts to users via email upon detecting human intrusion. The system comprises a PIR sensor, Pi camera, Raspberry Pi-3, and an Internet connection. There are two operational modes in the proposed security system. In the first mode, movement by an intruder is detected, and simultaneously, every time someone rings the doorbell, the Pi camera captures an image. The system then accesses a stored database to ascertain whether the individual is recognized. If the person is unfamiliar, the user receives an email notification, including the captured image of the individual. On the other hand, if the person is recognized, the system stores the captured image. In the second mode, when someone exhibits suspicious behaviour in front of the door, the system sends an alert email to the user, prompting them to activate the security alert system installed at the entrance. For face detection, we employ the Haar cascade technique. Face recognition involves two steps: feature extraction and classification. In the feature extraction phase, we compare various algorithms, and a comparative study of these provides a methodology that achieves 99.56% accuracy, outperforming other existing models. The developed system leverages the IoT platform to fortify security against intruders, thereby fostering a safe and secure environment.

Face recognition system has always been a crucial human-computer interaction tool in most security systems, access control, video surveillance, commercial areas, and networks like Facebook as well. After development in the area of artificial intelligence and growing security concerns, face recognition system has attracted attention by providing maximum efficiency in face detection and recognition. Face recognition is considered to be a biometric artificial intelligence-based application. Face recognition is the process of recognizing the face of a person by a vision system. As an extension to the existing face recognition system in this model, a new feature is added i.e., a voice message as output that is produced for each face recognized. The voice message could be anything like a simple hello or even a complex sentence. Keywords: Artificial intelligence, Face recognition, voice message, OpenCV, pyttsx.