LeakyPick: IoT Audio Spy Detector

Manufacturers of smart home Internet of Things (IoT) devices are increasingly adding voice assistant and audio monitoring features to a wide range of devices including smart speakers, televisions, thermostats, security systems, and doorbells. Consequently, many of these devices are equipped with microphones, raising significant privacy concerns: users may not always be aware of when audio recordings are sent to the cloud, or who may gain access to the recordings. In this paper, we present the LeakyPick architecture that enables the detection of the smart home devices that stream recorded audio to the Internet without the user's consent. Our proof-of-concept is a LeakyPick device that is placed in a user's smart home and periodically "probes" other devices in its environment and monitors the subsequent network traffic for statistical patterns that indicate audio transmission. Our prototype is built on a Raspberry Pi for less than USD40 and has a measurement accuracy of 94% in detecting audio transmissions for a collection of 8 devices with voice assistant capabilities. Furthermore, we used LeakyPick to identify 89 words that an Amazon Echo Dot misinterprets as its wake-word, resulting in unexpected audio transmission. LeakyPick provides a cost effective approach for regular consumers to monitor their homes for unexpected audio transmissions to the cloud

Taxonomic Classification of IoT Smart Home Voice Control

Voice control in the smart home is commonplace, enabling the convenient control of smart home Internet of Things hubs, gateways and devices, along with information seeking dialogues. Cloud-based voice assistants are used to facilitate the interaction, yet privacy concerns surround the cloud analysis of data. To what extent can voice control be performed using purely local computation, to ensure user data remains private? In this paper we present a taxonomy of the voice control technologies present in commercial smart home systems. We first review literature on the topic, and summarise relevant work categorising IoT devices and voice control in the home. The taxonomic classification of these entities is then presented, and we analyse our findings. Following on, we turn to academic efforts in implementing and evaluating voice-controlled smart home set-ups, and we then discuss open-source libraries and devices that are applicable to the design of a privacy-preserving voice assistant for smart homes and the IoT. Towards the end, we consider additional technologies and methods that could support a cloud-free voice assistant, and conclude the work

Smart Product Design Methodology

The noticeable emergence of new technological advances, such as Artificial Intelligence (AI) and Internet of Things (IoT), and their continuous developments in today’s market, have paved the way for an apparent transformation from conventional products to smart connected products. Smart products are Cyber-Physical Systems (CPS) that provide services to users through Internet and Communication capabilities. The use of smart products offers exceptional potential for the users to meet their expectations and needs intelligently and effectively. Hence, designers and manufacturers are encouraged to cope with constantly changing consumers’ requirements and help in satisfying their needs. It is necessary to achieve a high level of awareness when interacting with smart products, where in some cases, ambiguity and uncertainty may lead to an undesired outcome. Thus, the objective of this research thesis is to introduce a novel smart product design methodology that reveals a new design dimension that was found by conducting an extensive literature review. Smart product design methodology uses integration between existing Design Theory and Methodologies (DTM), both Systematic Design Approach (SDA) and Axiomatic Design Theory (ADT) which are integrated through the features and functions of smart products. The proposed design methodology concentrates on reducing the complexity of the product and raising its affordances for the users to perceive. This research includes a case study on smart speakers and voice-initiated virtual assistants specifically on Amazon’s Alexa, where the methodology proposed was applied. As a result, the complexity was reduced by achieving an uncoupled design, and affordances’ measures were discussed using the guidelines and recommendations concerning both visual and voice design perspectives for designers and developers of virtual assistants in order to maximize the affordances for the user to perceive with the least amount of ambiguity and doubtfulness

Design of passive SD modulator for ESP32

This thesis addresses the problem of voice recognition, by studying how to build a lowcost solution for data acquisition, presents the analysis, design implementation and simulation of a low-cost continuous-time(CT) passive sigma-delta modulator(SDM) with signal-to-noise-plus-distortion ratio(SNDR) > 86dB to increase fidelity in voice recognition applications. Employing passive RC integrators and a differential signal structure, the CT passive SDM is optimized to work as independently from a specific comparator module as possible, by decreasing the necessary gain of the comparator in the modulator gain. Nevertheless, the loop gain is restricted by the comparator’s noise, aggravated by the high attenuation of the passive RC integrators on the signal, causing low voltage swing at the comparator’s input. It is discussed the viability of utilizing a microprocessor (μP) as substitute of the comparator block in a CT passive SDM, specifically, the esp32. Due to hardware limitations and the high-frequency requirements of the CT passive SDM, it is proven this substitution is not viable. Along the course of the design implementation a comparison in the performance of three different simulation software is presented, these software being, the open-source LTspice VII, the open-source Ngspice and the private Cadence Virtuoso. As it was necessary to change simulation software at different stages in the design of the circuit

Home Automation with Personal Assistant

The Internet of Things (IoT) paradigm has been achieved in complex contexts, such as in the home automation market. Due to complexity in its working as well as huge internet traffic, the whole process is not long lasting and it becomes cumbersome to maintain the proper functioning of devices. Now-a-days, giant Techno-institutes are massively dependent on IoT based applications to provide better commercial as well as domestic e-products in terms of simplicity and feasibility. In the following project we have discussed a new methodology of Home Automation in which the electronic gadgets used in home environment as well as workplace can be controlled by the device itself. ?With a unique internet access point in the particular environment, the device is connected to the IP gateway so that it can be controlled from anywhere and any place with the help of proper internet connection. The IP address provided will not function for an individual device, but for the entire network to which all the devices are being accessed.?[1] The interconnection of all the devices can be enabled with the help of an open source software. Initially the device will act and remember the commands as given and will act accordingly. After some duration of time, it will automatically start the actions as previously in-scripted in its memory. Home automation not only helps to reduce human efforts but is also energy efficient and time saving. The main objective of home automation is to help handicapped and old aged people that will enable them to control home appliances and alert them in some immediate situations

The Emergence of Artificial Intelligence in the Home: Products, Services, and Broader Developments of Consumer Oriented AI

Current home automation system merges a family\u27s lifestyle with the latest technology & energy management tools to simplify people\u27s lives. It allows users to easily manipulate a variety of home systems, including appliances, security systems, and environmental systems. Setting up a home automation system confuses many consumers. Multiple product lines and platforms make choosing the best system difficult. Basic requirements of setting up a home automation system and the comparison between different platforms are explained. An intelligent home automation system makes intelligent decisions to control a home. This type system might use a weather report to adjust a home\u27s lawn watering schedule, as well as adjust the thermostat for temperature control in the home. Traditional home automation systems require human decision making to control the home system. The future intelligent home will require less human interactions, that can do things automatically after it learns patterns from us. A new generation requires more developed AI to control the smart home automation. Based on the technology we have now, the possible consumer-oriented AI technology is predicted in this paper. When the market is growing rapidly, companies are supposed to have better opportunities to make money. Due to the increasing popularity of home automation systems, the competition is very intense. Companies try the best to take the first mover advantage. Three suggestions are made to help those companies to build their strategies