A smart alarm system with internet-of-things

With the progress of the economy and society, people aspire to live in a safer, more convenient, and efficient environment, which has resulted in the integration of smart home technology into our daily lives. One of the most significant areas where technology can benefit us is in the domain of se...

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Bibliographic Details
Main Author: He, Chengwei
Other Authors: Chan Pak Kwong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167074
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Institution: Nanyang Technological University
Language: English
Description
Summary:With the progress of the economy and society, people aspire to live in a safer, more convenient, and efficient environment, which has resulted in the integration of smart home technology into our daily lives. One of the most significant areas where technology can benefit us is in the domain of security. There are many home security systems in the existing market, however, some of system may have issues such as expensive, ineffective and delay in alerting the user in the event of an unusual activity. In order to be effective, a security system must be capable of instantly alerting the user through phone or text in case of any unusual event. Therefore, in order to tackle the aforementioned concerns, this Final Year Project (FYP) aims to develop an advanced security alert system for smart homes based on the Internet of Things (IoT) technology with the ability to detect any unusual activity or intruders within the premises. This low-cost home security system employs two microcontrollers together with various sensors such as: Passive Infrared sensor, ultrasonic sensor etc. The microcontrollers will interface with various sensors and send a notification (image or text) to user via telegram or Blynk app when there is an abnormal event occurs. Furthermore, users can interact with the system through both mobile phone and web interfaces. The system's effectiveness is measured by its capacity to accurately detect security threats, achieving a precision rate of 95.2% and an accuracy rate of 97.5%.