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Smart Skins- Embedded Sensor Network cse400/CSE400_2013_2014/... Smart Skins- Embedded Sensor Network Dept. of CIS - Senior Design 2013-2014 Sunny Shah [email protected] Univ.

Nov 06, 2020

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  • Smart Skins- Embedded Sensor Network

    Dept. of CIS - Senior Design 2013-2014∗

    Sunny Shah [email protected]

    Univ. of Pennsylvania Philadelphia, PA

    Joel Goldman [email protected]

    Univ. of Pennsylvania Philadelphia, PA

    Geoffrey Vasudevan [email protected] Univ. of Pennsylvania

    Philadelphia, PA

    ABSTRACT Smart Skins attempts to solve the problem of home automa- tion. The problem is addressed in an object-oriented fashion where real-world objects are represented and interacted with as programming objects. The objects have various properties reflecting levels of temperature, vibration, sound and light. These properties are then utilized to make if/then statements dependent on object properties.

    The goal of Smart Skins is to provide a platform through which a user can intelligently interact with their appliances. It accomplishes this goal by utilizing a network of multi- purpose sensing devices that transmit sensor data to a web interface which, using a set of algorithms, displays the in- formation in a manner that allows the user to gain an un- derstanding beyond the core data.

    Furthermore, the system is calibrated to preserve battery without negatively effecting performance. This helps support our ‘̀pull’́ use-case where the user does not need to constantly interface with the Smart Skins device. Instead, the device will push useful information to the user at the appropriate time.

    1. INTRODUCTION Ubiquitous Computing and Smart Homes have been an

    active research area since Mark Weiser coined the term and its value proposition to users in a landmark paper [21]. His vision predicted that computing will infuse everyday objects to become ‘smart objects’ that unobtrusively and invisibly automate routine tasks on behalf of users. The vision led to much excitement in the Computer Science community. As a result, several university ‘live labs’ and a plethora of industry standards around sensor operating systems, net- work protocols and data interchange formats were created to jump start this new industry around home monitoring and automation [11, 4, 9]. Yet, in the two decades since the writing of Weiser‘s paper, there has been limited business success in the market.

    We believe this lack of a business impact is in large part because the technology architectures around smart homes have high switching costs. Previously, the only way to ‘smarten’ an appliance was to dispose of it and buy a new (and sub- stantially more expensive) ‘smart appliance’. By extension, the only way to convert a home to a smart home is to re- place appliances with new and smart counterparts. Most consumers have thousands of dollars of sunk cost in their home appliances, and the potential dream of a smart home

    ∗Advisor: Zachary Ives ([email protected]).

    is inadequate to lead them to make such a large capital in- vestment. The “Internet of Things” market was validated to a greater extent in late 2013, early 2014 with the $3.2 billion acquisition of Nest by Google as well as the fact that over $1 billion in U.S. venture capital money (3% of the to- tal) has been invested into this market [18]. Nest has shown the power of organic replacement of a few key objects with smart counterparts (e.g. Thermostat and carbon monoxide detector). Twine has been first to the market in demon- strating the ability to enhance legacy appliances with smart skins [10, 13].

    Smart Skins fits into the scope of the “Internet of Things” market where physical objects are made ‘smart’ through some type of interface with software. The device utilizes sound, light, vibration and temperature sensors connected to a WiFi enabled micro-controller to gather appliance data which is then passed to a web interface where it is analyzed and acted upon. This project predicts that Twine style ap- pliance skins will be the most effective method of smartening appliances and as such aims to improve on appliance skin performance in the following ways:

    • Smart Wake Up: Constant operation of sensor hard- ware is expensive and wasteful in terms of (battery) power. Most household washing machines run less than 5% of the week, and a sensor that is monitor- ing them 100% of the time is likely to require frequent battery replacement. Of course, this is unacceptable when considering the maintenance cost-to-device ben- efit ratio. Smart Skins utilizes a set of algorithms to determine the necessary amount of sensory data and through a feedback loop updates the device code so that the device posts only when necessary.

    • Smarter Device Models: While appliance state data provides an interesting interface for the user, the abil- ity to act on the data enhances the use cases for a consumer. Smart Skins, through Twilio and the Belkin Smart Switch allows users to receive text messages and toggle a switch based on the state of an appliance, mul- tiple appliances, time of day and other parameters [7, 5]. The design of Smart Skins also allows for easy ad- dition of other actuators and additional logic.

    • Monitor Device Collectives: Frequently, fulfilling a home monitoring need requires coordination across multiple smart objects. An example of this would be a washer and dryer, if the washer has completed its cycle and the dryer is off then this is valuable information to the user. Facilitating such device collectives requires

  • a ‘workflow’ layer, so that a combined behavior across a collection of devices can be verified for the end user. Smart Skins flexible cloud based implementation al- lows for a seamless workflow layer, where logical state- ments can be applied utilizing the IFTTT protocol and multiple appliance data.

    2. RELATED WORK The related work to Smart Skin falls into four categories

    • Projects that have utilized contactful sensors similar to Smart Skins

    • Projects that have utilized contactless sensors for de- tection

    • Advancement in component technologies that are ap- plicable to Smart Skins

    • Sensor industry standards that have end goals relevant to Smart Skins but have had mixed records of success in jump starting a Home Monitoring industry.

    In the first category of similar system architectures, there exists Twine and Spotter as notable Smart Skins datapoints. Twine and Spotter rely on contactful skinning where the skin is tethered to the device it is monitoring and each device has its own skin. Smart Skins uses these projects as a basis for the desired level of effectiveness while improving the battery life and implementing additional capabilities.

    In contrast to the contactful technologies, TinyEARS has adopted audio based technologies for contactless skinning, where the appliance skin can listen in on the appliance with- out being tethered to it. This technology allows for fewer sensors to be used, but is more susceptible to random noise. While there is long-term potential of well executed contact- less sensing, there are formidable noise interference chal- lenges that make audio sensing unsuitable as a near to medium term goal for the industry. The advancement in component technologies allows sensor skins to exist as they do. The continuing shrinking of microcontrollers as well as sensors allow these skins to comfortably fit on appliances without being obtrusive. The advancements in low-power Wi-Fi al- low the skins to run wirelessly for longer periods of time [19]. The combination of these improvements makes Smart Skins a viable option. The final category consists of indus- try standards such as Zigbee that were explicitly targeted towards the home but did not gain traction, perhaps because they were too complicated and both chip and software lev- els to provide a return on investment in the end-markets of home automation [16]. Active RFIDs were similarly seen as a promising technology for an “Internet of Things” but have yet to take off because of challenges within the open source community. The community was unable to motivate rapid use and build compelling apps around these ideas. Smart Skins is designed on the belief that technologies that are widely deployed in the industry and/or have a strong fol- lowing in the open source community have a better chance of being the basis for a home monitoring industry.

    3. SYSTEM MODEL The Smart Skin system is made up of three main compo-

    nents, the hardware device, the server with which the device and web application communicate and the web application itself.

    Figure 1: Model-View-Controller

    3.1 Overall This Smart Skins system consists of a network of sensor

    embedded devices linked to a remote web server. This web server interacts with a web application. Overall, this sys- tem can be represented within the Model-View-Controller (MVC) software pattern with slight modifications. The model is composed of the database, the view is the web applica- tion and the controller is the all of the scripts running on a server. The sensor network touches only the controller, but both provides input like a user and is manipulated by the controller like the model. More specifically the data can be thought of as traveling through three layers, the input later the API/Scripts layer and the database layer. This data flow is illustrated in Figure 1.

    3.2 Input Layer The input layer is made up of the web application and the

    device. The web application allows for the user to both pro- vide input (create account, login, set time zone, add device, delete device, change appliance for a device) and observe output (current state of appliances, previous state of appli- ances). A majority of the display and user interface of the web application has been developed, and allows for the ease of both user input as defined above

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