Social distancing and quarantining are now standard practices which are implemented worldwide since the outbreak of the novel coronavirus (COVID-19) disease pandemic in 2019. Due to the full acceptance of the above control practices, frequent hospital contact visits are being discouraged. However, there are people whose physiological vital needs still require routine monitoring for improved healthy living. Interestingly, with the recent technological advancements in the areas of Internet of Things (IoT) technology, smart home automation, and healthcare systems, contact-based hospital visits are now regarded as non-obligatory. To this end, a remote smart home healthcare support system (ShHeS) is proposed for monitoring patients' health status and receiving doctors’ prescriptions while staying at home. Besides this, doctors can also carry out the diagnosis of ailments using the data collected remotely from the patient. An Android based mobile application that interfaces with a web-based application is implemented for efficient patients-doctors dual real-time communication. Sensors are incorporated in the system for automatic capturing of physiological health parameters of patients. Also, a hyperspace analogue to context (HAC) was incorporated into the current monitoring framework for service discovery and context change in the home environment towards accurate readings of the physiological parameters and improved system performance. With the proposed system, patients can be remotely monitored from their homes, and can also live a more comfortable life through the use of some features of smart home automation devices on their phones. Therefore, one main significant contribution of this study is that patients in self-isolation or self-quarantine can use the new platform to send daily health symptoms and challenges to doctors via their mobile phones. Thus, improved healthy living and a comfortable lifestyle can still be achieved even during such a problematic period of the 2019 COVID-19 pandemic that has already recorded 20,026,186 million cases so far with 734,020 thousand deaths globally.
The smart home is now an established area of interest and research that contributes to comfort in modern homes. With the Internet being an essential part of broad communication in modern life, IoT has allowed homes to go beyond building to interactive abodes. In many spheres of human life, the IoT has grown exponentially, including monitoring ecological factors, controlling the home and its appliances, and storing data generated by devices in the house in the cloud. Smart home includes multiple components, technologies, and devices that generate valuable data for predicting home and environment activities. This work presents the design and development of a ubiquitous, cloud-based intelligent home automation system. The system controls, monitors, and oversees the security of a home and its environment via an Android mobile application. One module controls and monitors electrical appliances and environmental factors, while another module oversees the home’s security by detecting motion and capturing images. Our work uses a camera to capture images of objects triggered by their motion being detected. To avoid false alarms, we used the concept of machine learning to differentiate between images of regular home occupants and those of an intruder. The support vector machine algorithm is proposed in this study to classify the features of the image captured and determine if it is that of a regular home occupant or an intruder before sending an alarm to the user. The design of the mobile application allows a graphical display of the activities in the house. Our work proves that machine learning algorithms can improve home automation system functionality and enhance home security. The work’s prototype was implemented using an ESP8266 board, an ESP32-CAM board, a 5 V four-channel relay module, and sensors.
Security of lives and properties is highly important for enhanced quality living. Smart home automation and its application have received much progress towards convenience, comfort, safety, and home security. With the advances in technology and the Internet of Things (IoT), the home environment has witnessed an improved remote control of appliances, monitoring, and home security over the internet. Several home automation systems have been developed to monitor movements in the home and report to the user. Existing home automation systems detect motion and have surveillance for home security. However, the logical aspect of averting unnecessary or fake notifications is still a major area of challenge. Intelligent response and monitoring make smart home automation efficient. This work presents an intelligent home automation system for controlling home appliances, monitoring environmental factors, and detecting movement in the home and its surroundings. A deep learning model is proposed for motion recognition and classification based on the detected movement patterns. Using a deep learning model, an algorithm is developed to enhance the smart home automation system for intruder detection and forestall the occurrence of false alarms. A human detected by the surveillance camera is classified as an intruder or home occupant based on his walking pattern. The proposed method’s prototype was implemented using an ESP32 camera for surveillance, a PIR motion sensor, an ESP8266 development board, a 5 V four-channel relay module, and a DHT11 temperature and humidity sensor. The environmental conditions measured were evaluated using a mathematical model for the response time to effectively show the accuracy of the DHT sensor for weather monitoring and future prediction. An experimental analysis of human motion patterns was performed using the CNN model to evaluate the classification for the detection of humans. The CNN classification model gave an accuracy of 99.8%.
Smart home is an evolving technological innovation that originates from the numerous application areas of the Internet of Things (IoT). As the world is driving more and more closer to adopting smart cities based infrastructural environments, in which most activities involve innovative technological connectivity, smart home automation is one of the focused areas which has grown exponentially in the last few decades. The main objective of smart home automation is to make life easier and convenient for homeowners and users. The role of smart home automation is essential to healthcare and the social and economic well-being of all users through the provision of a convenient and conducive place of living. With the spontaneous evolution of new trends in smart home automation design, the various elements and functions of devices used in building smart home systems need to be explained as these technologies have significant benefits. They can assist traditional methods of controlling and monitoring home appliances, improve healthcare for the elderly and disabled, alert homeowners in case of potential risk and enable homes to be controlled even while the owner is far from home. Most importantly, smart home systems have great potential for reduction in energy loss. Furthermore, to provide valuable insights into these technological environments, we must clearly understand some of the available options and gaps in the area of smart home automation systems. This paper presents a taxonomy of IoT smart home automation systems with elaborate discussions on the technologies, trends and challenges in smart home automation system design. A constructive and detailed review of existing literature based on application areas of smart home automation is presented. Lastly, highlights of the approaches, technologies, and strength and weaknesses associated with the smart home automation systems are discussed.
The use of modern technologies for control and monitoring and accessing devices in domestic or industrial buildings with convenience, comfortable and easy access from any location is the primary aim of the internet of things (IoT) technology for smart home automation. Complete Smart home automation, with overall control from any place at any time is still not fully available. Nevertheless, this work proposes a mobile application system for smart homes, with the purpose of overall monitoring and control of home appliances and devices. The proposed method is based on Zigbee, Arduino and Bluetooth for wireless communication among devices in the home. At the same time, a mobile application is used for the control and monitoring of the devices or appliances. In this study, Zigbee and Bluetooth are combined in order to establish efficient communication either within or outside the home premises. A user scenario of the proposed work was simulated using Proteus Simulation software to validate the practicability of the new system.
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