This study explores the use of natural language to give instructions that might be interpreted by Internet of Things (IoT) devices in a domestic smart home' environment. We start from the proposition that reminders can be considered as a type of end-user programming, in which the executed actions might be performed either by an automated agent or by the author of the reminder. We conducted an experiment in which people wrote sticky notes specifying future actions in their home. In different conditions, these notes were addressed to themselves, to others, or to a computer agent.We analyse the linguistic features and strategies that are used to achieve these tasks, including the use of graphical resources as an informal visual language. The findings provide a basis for design guidance related to end-user development for the Internet of Things.
There is a long tradition of exploring the potential design space of smart home' technologies through study of natural behaviours in the home (e.g. @cite_6 ), and investigating the ways in which families respond to the opportunity to program and configure existing digital technologies @cite_5 . Sticky notes are often included in the kit of materials for cultural probe studies (e.g. @cite_14 ), and the sticky note metaphor has been literally rendered in home technology probes (e.g. @cite_17 ). The refrigerator door, as a location where sticky notes and other papers are placed, is a regular focus of smart home technology, both as a versatile augmented display surface for research attention @cite_18 and more literally in commercial products such as the Samsung WiFi-enabled fridge http: www.samsung.com us topic apps-on-your-fridge . One can imagine that sticky notes themselves might be used as an EUP technology in future (e.g. @cite_15 ), and there are many previous systems that have augmented sticky notes in ways that might achieve this (e.g. as reviewed by @cite_10 ).
@cite_18 @cite_14 @cite_6 @cite_5 @cite_15 @cite_10 @cite_17
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In this paper we present a number of augmented refrigerator magnet concepts. The concepts are shown to be derived from previous research into the everyday use of fridge surfaces. Three broadly encompassing practices have been addressed through the concepts: (i) organization planning in households; (ii) reminding; and (iii) methods household members use to assign ownership to particular tasks, activities and artifacts. Particular emphasis is given to a design approach that aims to build on the simplicity of magnets so that each of the concepts offers a basic, simple to operate function. The concepts, and our use of what we call this less is more design sensibility are examined using a low-fidelity prototyping exercise. The results of this preliminary work suggest that the concepts have the potential to be easily incorporated into household routines and that the design of simple functioning devices lends itself to this. We describe a novel method for symbolic location discovery of simple objects. The method requires no infrastructure and relies on simple sensors routinely used in sensor nodes and smart objects (acceleration, sound). It uses vibration and short, narrow frequency 'beeps' to sample the response of the environment to mechanical stimuli. The method works for specific locations such as 'on the couch', 'in the desk drawer' as well as for location classes such as 'closed wood compartment' or 'open iron surface'. In the latter case, it is capable of generalizing the classification to locations the object has not seen during training. We present the results of an experimental study with a total of over 1200 measurements from 35 specific locations (taken from 3 different rooms) and 12 abstract location classes. It includes such similar locations as the inner and outer pocket of a jacket and a table and shelf made of the same wood. Nonetheless on locations from a single room (16 in the largest one) we achieve a recognition rate of up to 96 . It goes down to 81 if all 35 locations are taken together, however the correct location is in the 3 top picks of the system 94 of the times. Device-free localization (DFL) enables localizing people by monitoring the changes in the radio frequency (RF) attenuation field of an area where a wireless network is deployed. Notably, this technology does not require people to participate in the localization effort by carrying any electronic device. This paper presents a DFL system for long-term residential monitoring. Due to the daily activities carried out by the people being monitored, the radio signals' propagation patterns change continuously. This would make a system relying only on an initial calibration of the radio environment highly inaccurate in the long run. In this paper, we use an on-line recalibration method that allows the system to adapt to the changes in the radio environment, and then provide accurate position estimates in the long run. A finite-state machine (FSM) defines when the person is located at specific areas-of-interest (AoI) inside the house (e.g. kitchen, bathroom, bed, etc.). Moreover, each time a state transition is triggered, the system tweets the new AoI in a Twitter account. The FSM allows extracting higher level information about the daily routine of the person being monitored, enabling interested parties (e.g. caretakers, relatives) to check that everything is proceeding normally in his life. In the long-term experiment carried out in a real domestic environment, the system was able to accurately and reliably localize the person during his daily activities. This study investigates replication of data in a novel streaming architecture consisting of ad-hoc networks of wireless devices. One application of these devices is home-to-home (H2O) entertainment systems where a device collaborates with others to provide each household with on-demand access to a large selection of audio and video clips. These devices are configured with a substantial amount of storage and may cache several clips for future use. A contribution of this study is a technique to compute the number of replicas for a clip based on the square-root of the product of bandwidth required to display clips and their frequency of access , i.e., where . We provide a proof to show this strategy is near optimal when the objective is to maximize the number of simultaneous displays in the system with string and grid (both symmetric and asymmetric) topologies. We say “near optimal” because values of less than 0.5 may be more optimum. In addition, we use analytical and simulation studies to demonstrate its superiority when compared with other alternatives. A second contribution is an analytical model to estimate the theoretical upper bound on the number of simultaneous displays supported by an arbitrary grid topology of H2O devices. This analytical model is useful during capacity planning because it estimates the capabilities of a H2O configuration by considering: the size of an underlying repository, the number of nodes in a H2O cloud, the representative grid topology for this cloud, and the expected available network bandwidth and storage capacity of each device. It shows that one may control the ratio of repository size to the storage capacity of participating nodes in order to enhance system performance. We validate this analytical model with a simulation study and quantify its tradeoffs.