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  Automated Low-Cost Home Sensing with E-mail Capability: A new Perspective to Remote Home Sensing for Surveillance  
  Authors : John Francis Ogbonoko; Abdulkadir Dauda; Haruna Umar Adoga
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This research focuses on the application of Internet of Things in remote home sensing with the design and implementation of a system built around WiFi infrastructure. It also focused on the strength of the microcontroller - Raspberry Pi in building IoT systems. The developed system is made up of two parts; the hardware part that is powered by Raspberry Pi. This provides the appropriate interface for connecting the sensors, pi-camera module, and other hardware devices of the system. The second part which is more of the programming aspect implemented using Python is the distance measurement, image capture, and email application that provides the interface for home surveillance and monitoring against burglary, and for appropriate actions to be taken by the home owner. The system is scalable, adaptable, and cost effective compared to the commercially available systems found in the market for the same purpose. It is also easy to build by anyone if the implementation procedures outlined in this work are followed through correctly.


Published In : IJCSN Journal Volume 8, Issue 1

Date of Publication : February 2019

Pages : 28-35

Figures :11

Tables : 01


Ogbonoko, J. F. : holds a Bachelor of Science (BSc.) degree in Computer Science from the Benue State University, Makurdi, Nigeria. He also holds a Master of Science (MSc.) degree in Software Systems and Internet Technology from the University of Sheffield, United Kingdom. He currently lectures in the Department of Computer Science, Federal University Lafia, Nasarawa State, Nigeria. His research interests are in the area of Software Engineering, Internet of Things, and Big Data.

Abdulkadir Dauda : was born in Lafia, Nasarawa State of Nigeria on the 25th of October 1982. He obtained the Bachelor of Science degree in Computer Science from the Usmanu Danfodiyo University Sokoto, Nigeria in 2006. He worked with the Nigerian Judiciary as a Programme Analyst from February 2009 to April 2014 when he joined the Federal University Lafia as a Graduate Assistant. In 2015, he proceeded to the University of Bedfordshire, United Kingdom for his Masters of Science Degree which he completed in January 2017. He currently works as an Assistant Lecturer in the department of Computer Science, Federal University Lafia, Nigeria. His research interests are in the area of High-Performance Computing and Distributed Systems.

Adoga, H. U. : holds a Bachelor of Engineering (B.Eng.) in Electrical & Electronics Engineering from the University of Maiduguri, Nigeria, with specialization in data communications and networks. He also holds a Master of Science (MSc.) degree in Computer Science, from the University of Hertfordshire, England. He is currently a lecturer with the Department of Computer Science, Federal University Lafia, Nigeria. His research interests are in the areas of Software Defined Networking (SDN), IOT and Distributed Systems. He is a registered member of the Institute of Electrical and Electronics Engineers (IEEE), the Nigeria Computer Society (NCS), and the Nigeria Society of Engineers (NSE). As a CCNP professional, Haruna is also fascinated by design and configuration of computer networks.


Internet of Things, Home sensing, Raspberry Pi, Python, Sensor Networks, Computer Networks

There is still much to be desired as far as home sensing for surveillance and monitoring is concerned. In the work carried out, the authors have successfully deployed Raspberry Pi and Python programming language to build a low-cost home sensing system. However, it is important to note that the system is scalable to accommodate a database that holds the distances measured, links to the images captured in the image folder, links to the email notification, and a web interface for controlling the system. It is possible to also extend functionality to a web interface that provides users with an option to take appropriate action, for example, to alert the nearest police station for arrest of burglars or intruders. Another consideration would be to have a module that scans images captured to be matched with images in a crime database for identification of burglars and intruders.


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