Abstract
The extensions of the environment with the integration of sensing systems in any space, in conjunction with ubiquitous computing are enabling the so-called Smart Space Sensor Networks. This new generation of networks are offering full connectivity with any object, through the Internet of Things (IoT) and/or the Web, i.e., the Web of Things. These connectivity capabilities are making it feasible to sense the behaviours of people at home and act accordingly. These sensing systems must be integrated within typical elements found at home such as furniture. For that reason, this work considers furniture as an interesting element for the transparent location of sensors. Furniture is a ubiquitous object, i.e., it can be found everywhere at home or the office, and it can integrate and hide the sensors of a network. This work addresses the lack of an exhaustive study of the effect of furniture on signal losses. In addition an easy-to-use tool for estimating the robustness of the communication channel among the sensor nodes and gateways is proposed. Specifically, the losses in a sensor network signal due to the materials found within the communication link are evaluated. Then, this work proposes a software tool that gathers the obtained results and is capable of evaluating the impact of a given set of materials on the communications. This tool also provides a mechanism to optimize the sensor network deployments during the definition of smart spaces. Specifically, it provides information such as: maximum distances between sensor nodes, most suitable type of furniture to integrate sensors, or battery life of sensor nodes. This tool has been validated empirically in the lab, and it is currently being used by several enterprise partners of the Technological Centre of Furniture and Wood in the southeast of Spain.
Highlights
An extended range of new sensing applications and solutions have emerged in different fields such as rural and forest fire detection [1], monitoring of industrial manufacturing processes [2], transport/logistics [3], and for personal services in areas such as healthcare and Ambient AssistedLiving (AAL) [4]
The first advantage is that this allows the definition of ubiquitous can be more achieved when sensor nodes are integrated in furniture, since the user will not perceive the existence of these devices, as mentioned by Mark Weiser, the father of the ubiquitous computing, “Hundreds of computers in a room could seem intimidating at first, just as hundreds of volts coursing through wires in the walls did at one time
The Link Quality Index (LQI) concept is similar to Received Signal Strength Indication (RSSI), since it is an estimate of the quality of the communication link
Summary
An extended range of new sensing applications and solutions have emerged in different fields such as rural and forest fire detection [1], monitoring of industrial manufacturing processes [2], transport/logistics [3], and for personal services in areas such as healthcare and Ambient AssistedLiving (AAL) [4]. These new advanced applications based on a new generation of sensing and communication capabilities are a consequence of the continuous advances in sensor technologies and wireless communication protocols that allow for greater autonomy of sensor nodes One of these application areas has focused on Wireless Sensor Networks (WSNs) in the users’ environment, such as their home, in order to provide monitoring or assistance in everyday tasks and situations through the denominated Ambient Intelligence (AmI) [5,6]. Some pieces of furniture can be in contact with the user, which provides an ideal situation for measuring certain types of variables (e.g., user location, and temperature) This integration of the sensors in typical home objects in conjunction with the capabilities to communicate with remote servers and services provide a high quantity and better quality of data for AmI systems
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