Smart Home Hubs Research Articles

Design and Implementation of Home Automation using Amazon Alexa

Abstract: The design and implementation of a home automation system using Amazon Alexa, a voice-controlled virtual assistant. With the rapid growth of smart home technology, integrating voice control capabilities has become a popular and convenient way to interact with home automation systems. The proposed system leverages the power of Amazon Alexa to enable users to control and monitor various household appliances through voice commands. The system consists of a cloud-based backend for data storage and processing, a smart home hub for device control, and a mobile application for user interaction. The hardware and software components, including devices, sensors, and communication protocols, are carefully selected and integrated into the system. The integration with Amazon Alexa Skills Kit allows the system to understand and process voice commands effectively. A case study is presented to demonstrate the practical application of the system in a typical home environment. The results showcase the system's efficiency, convenience, and user satisfaction. This project contributes to the growing field of home automation and highlights the potential of voice-controlled virtual assistants like Amazon Alexa in improving the functionality and usability of smart homes. The proposed system encompasses a cloud-based backend, a smart home hub, and a mobile application to facilitate seamless control and monitoring of various household appliances and devices through voice commands. The selection and integration of appropriate hardware and software components, including devices, sensors, and communication protocols, are thoroughly discussed. Furthermore, the system is integrated with the Amazon Alexa Skills Kit to enable effective processing of voice commands. A detailed case study is presented, highlighting the system's practical application within a typical home environment. The results demonstrate the system's efficacy, emphasizing its convenience, efficiency, and user satisfaction. This project contributes to the ever-growing field of home automation, showcasing the potential of voice-controlled virtual assistants, such as Amazon Alexa, to enhance the functionality and user experience of smart homes. Future enhancements and research directions are also discussed, paving the way for further advancements in this domain.

The Fusion of Health Tech and Insure Tech

Digital technology has increasingly grown smaller – from the age of large computers, we now have digitalized devices that can be worn on the human body. Such digital devices that aid in healthcare have been seeing a rapid adoption. Today, it is difficult to have a walk in a park without witnessing several people wearing fitness bands on their wrists. While such technology is making it easier for users to track their health, the aggregated data when collected over the internet can be a treasure trove of information, which insurance companies are trying to mine. From $5.18 billion in 2014, the global market of IoT Healthcare Technology is poised to be over $14.6 billion by the end of 2022 as per Zion Market Research. Other types of health technology such as smartphone apps, connected health devices, smart home hubs, and so on also act as sources of data. Insurance has always been a very data-driven industry. As such, insurance product managers have always been on the look-out of newer data sources in order to obtain different types of insights for shaping their product development strategy. Therefore, the insurance sector is eagerly exploring the possibilities of using data collected from wearable devices and other health technologies as such data was previously impossible to obtain. Not only does this aid in preventive healthcare, as people at high risk of certain ailments could be alerted in advance, but it also can help insurers to devise plans that can serve their intended beneficiaries better.

SoK: Privacy-enhancing Smart Home Hubs

Smart homes are IoT systems enabling the automation of household operation. The unrestricted collection and processing of data by smart home systems raises legitimate privacy concerns for their users. Over the past decade, there has been significant interest in privacy-enhancing technologies applied at the level of a local smart hub physically located in the home and acting as a gateway between sensors, applications, platform providers, and services in the cloud. The number and variety of projects and research proposals can, however, make their comparison a daunting and unnecessarily complex task. We systematize existing knowledge in this field through the analysis and categorization of 10 industrial and community-contributed systems and 37 research proposals from the literature of the past 11 years. Our results shed light on the diversity of system and trust models considered in the state-of-the-art and on the associated privacy-enhancing technologies. We further identify open research problems and promising approaches that would benefit the smart home hub model and the protection of smart home users’ privacy.

Privacy invasion via smart-home hub in personal area networks

Smart-home devices are being increasingly used in our daily lives. While these devices provide convenient functions to users, such convenience may come at a greater cost, such as the leakage of the user’s private information. This paper presents a system ChatterHub to address privacy risks in smart-home devices. Specifically, this work focuses on the devices that use Zigbee or Z-wave and are controlled by a centralized smart-home hub in a personal area network (PAN) for connecting to the Internet. ChatterHub passively eavesdrops on encrypted network traffic from the hub and leverages machine learning techniques to classify events and states of smart-home devices. We deployed ChatterHub on three real-world smart-home settings to evaluate its accuracy and efficiency. The evaluation results show that the attacker can successfully disclose smart-home devices’ behaviors with over 89% of recall and F1-score. We also demonstrate that an attacker can interfere with the smart-home hub’s communication and selectively drop packets to disable alerting users of a device’s status, such as security sensors and smart-locks. Furthermore, as a mitigation approach, we developed a packet-injection approach to effectively prevent threats from ChatterHub by generating only 9.2 MB of extra network traffic per day.

WISE: MQTT-based Protocol for IP Device Provisioning and Abstraction in IoT Solutions

Although numerous consumer devices use Transmission Control Protocol/Internet Protocol (TCP/IP) protocol stack to connect and communicate over the Internet, their integration into a single Internet of Things (IoT) solution represents a challenge, primarily due to the lack of the standardized interoperability framework on the application layer. Devices produced by different manufacturers cannot operate together out of the box, thus raising the cost of system setup and maintenance. In this paper, a novel protocol is proposed that aims to bridge this gap. It is based on Message Queuing Telemetry Transport (MQTT) protocol and allows the seamless integration of different kinds of IP devices into the connected system. The proposed protocol is complete as it covers the aspects of device discovery and association in the IoT network. It provides mechanisms for IoT network maintenance and defines the abstract device model and communication patterns to enable system-wide device interoperability. The other goal of the protocol is to be portable to resource-constrained platforms. To validate the proposed protocol, it was integrated into the existing smart home hub, and for testing and validation purposes, prototype devices were developed.

Cost Oriented Humanoid Robot communication with IoT devices via MQTT and interaction with a Smart Home HUB connected devices

The article describes different approaches for connecting the teen sized humanoid robot Archie with IoT devices. Main goal of the project is to develop a cost oriented autonomous humanoid robot to assist humans in daily life tasks, thus Archie robot’s natural habitat will be our homes and workplaces. Methods for ROS integration of remote internet enabled sensors, actuators and other devices are described. Test with real life use cases are performed. MQTT M2M protocol have been used for connecting to internet enabled IoT devices. Smart home hubs, which connect either locally or to the cloud, IoT devices, that use the Zigbee or Z-Wave and other protocols, rather than only Wi-Fi connected devices, are disused. Finally, we have successfully implemented and tested 3 different approaches for connecting Archie robot to IoT devices, which gives the robot the ability to interact with the environment by receiving data and the ability to control the thousands of IoT devices available on the market.

PrivHome: Privacy-Preserving Authenticated Communication in Smart Home Environment

A smart home enables users to access devices such as lighting, HVAC, temperature sensors, and surveillance camera. It provides a more convenient and safe living environment for users. Security and privacy, however, is a key concern since information collected from these devices are normally communicated to the user through an open network (i.e. Internet) or system provided by the service provider. The service provider may store and have access to these information. Emerging smart home hubs such as Samsung SmartThings and Google Home are also capable of collecting and storing these information. Leakage and unauthorized access to the information can have serious consequences. For example, the mere timing of switching on/off of an HVAC unit may reveal the presence or absence of the home owner. Similarly, leakage or tampering of critical medical information collected from wearable body sensors can have serious consequences. Encrypting these information will address the issues, but it also reduces utility since queries is no longer straightforward. Therefore, we propose a privacy-preserving scheme, $\sf {PrivHome}$ PrivHome . It supports authentication, secure data storage and query for smart home systems. $\sf {PrivHome}$ PrivHome provides data confidentiality as well as entity and data authentication to prevent an outsider from learning or modifying the data communicated between the devices, service provider, gateway, and the user. It further provides privacy-preserving queries in such a way that the service provider, and the gateway does not learn content of the data. To the best of our knowledge, privacy-preserving queries for smart home systems has not been considered before. Under our scheme is a new, lightweight entity and key-exchange protocol, and an efficient searchable encryption protocol. Our scheme is practical as both protocols are based solely on symmetric cryptographic techniques. We demonstrate efficiency and effectiveness of our scheme based on experimental and simulation results, as well as comparisons to existing smart home security protocols.

Welcome pwn: Almond smart home hub forensics

Many home interactive sensors and networked devices are being branded as “Internet of Things” or IoT devices. Such disparate gadgets often have little in common other than that they all communicate using similar protocols. The emergence of devices known as “smart home hubs” allow for such hardware to be controlled by non-technical users providing inexpensive home security and other home automation functions. To the cyber analyst, these smart environments can be a boon to digital forensics; information such as interactions with the devices, sensors registering motion, temperature or moisture levels in different rooms, all tend to be collected in one central location rather than separate ones. This paper presents the research work conducted on one such smart home hub environment, the Securifi Almond+, and provides guidance for forensic data acquisition and analysis of artefacts pertaining to user interaction across the hub, the iPhone/Android companion applications and the local & cloud-based web interfaces.

Visible Light Identification System for Smart Door Lock Application with Small Area Outdoor Interface

Visible light identification (VLID) is a user identification system for a door lock application using smartphone that adopts visible light communication (VLC) technology with the objective of high security, small form factor, and cost effectiveness. The user is verified by the identification application program of a smartphone via fingerprint recognition or password entry. If the authentication succeeds, the corresponding encoded visible light signals are transmitted by a light emitting diode (LED) camera flash. Then, only a small size and low cost photodiode as an outdoor interface converts the light signal to the digital data along with a comparator, and runs the authentication process, and releases the lock. VLID can utilize powerful state-of-the-art hardware and software of smartphones. Furthermore, the door lock system is allowed to be easily upgraded with advanced technologies without its modification and replacement. It can be upgraded by just update the software of smartphone application or replacing the smartphone with the latest one. Additionally, wireless connection between a smartphone and a smart home hub is established automatically via Bluetooth for updating the password and controlling the home devices. In this paper, we demonstrate a prototype VLID door lock system that is built up with LEGO blocks, a photodiode, a comparator circuit, Bluetooth module, and FPGA board.