This paper describes the development of a Smart Sleeve control mechanism for Active Assisted Living. The Smart Sleeve is a physically worn sleeve that extends the user's control capability within his/her intelligent built-environment by enabling (1) direct actuation and/or (2) teleoperation via a virtual interface. With respect to the first, the user may point his/her sleeve-wearing arm towards a door or a window and actuate an opening or a shutting; or towards a light and effect its turning on and off as well as regulating its intensity; or even towards a particular region to initiate ventilation of it. With respect to the second, the user may engage actuations in systems beyond his/her field of vision by interacting with a virtual representation of the intelligent built-environment projected on any screen or surface. For example, the user is able to shut the kitchen's door from his/her bedroom by extending the Smart Sleeve towards the door of a virtual representation of the kitchen projected (via a standard projector and/or television monitor) on the bedroom's wall. In both cases, the Smart Sleeve recognizes the object which the user wishes to engage with-whether in the real or the virtual worlds-(a) by detecting the orientation of the extended arm via an Accelerometer / Gyroscope / Magnetometer sensor; and (b) by detecting a specific forearm muscle contraction via Electromyography caused by the closing and opening of the fist, which serves to select the object. Once the object is identified and selected with said muscle contraction, subsequent arm gestures effect a variety of possible actuations for a given object (e.g., a window may be opened / shut or dragged to differing degrees or aperture; a light's intensity may be increased or decreased, etc.). In cases of ambiguous selections, the user my use voice-commands to explicitly identify the desired object of selection. Furthermore, due to this voice-based recognition mechanism, which recognizes both spoken commands as well the identity of the speakers, different rights to actuation may be assigned to different users. The Smart Sleeve is yet another mechanism integrated into an on-going development of a highly intuitive Active and Assisted Living implementation and its features, ones explicitly designed to enhance user-experience as well as to promote user well-being via intuitive interactions between human and non-human agents within the intelligent built-environment.@en

This paper details a proof-of-concept development of an adaptive staircase system-type capable of user-specific mechanical reconfigurations actuated by facial-, object-, and voice-recognition. The system is described via two variation-prototypes - developed at Technology Readiness Level 4 - as instances of the same system-type. Accordingly, each prototype is informed by the same use-case considerations and requirements. Nevertheless, by means of their mechanical particulars, advantages and disadvantages specific to each variation are identified and explored. The present adaptive staircase system-type consists of two main components, one computational and the other mechanical. The computational component is built upon an inherited System Architecture previously developed and implemented by the authors. More specifically, the computational component uses Google's TensorFlow for facial-recognition; BerryNet for multi-object detection; and VoiceIt for voice-recognition. These three cloud-compatible, -based, or -dependent recognition mechanisms are used to ascertain the identity three user-types: (1) a person without perceivable physical disabilities; (2) a person reliant on a walking-cane; and (3) a person on a wheelchair. With the exception of the first case, the computational component proceeds to actuate mechanical transformations pertinent to each variety of disabilities depending on which user-type is identified. The objective of this implementations is to present an intuitive and automated vertical mobility solution capable of supporting users with varying degrees of reduced mobility.@en

This paper presents a context-Aware light-Tracking and-redirecting system guided by hand-gesture recognition. It is conceived as yet another mechanism within an ongoing development of a more intuitive and technically sophisticated Ambient Intelligence / Active and Assisted Living ecosystem. The detailed system consists of individual nodes that are strategically installed across regions of a building-envelope, which enables this latter to draw or deflect direct natural light into or away from specific locations within the built-environment as requested by the user(s) via recognized hand-gestures. Each node is capable of sending and receiving sensed-data continuously via ZigBee with one another as well as with microcontrollers embedded within the interior built-environment. Said microcontrollers are equipped with cameras via which four hand-gestures may be recognized. The first or initializing hand-gesture engages the system and enables it to recognize any of the remaining hand-gestures. The second redirects light towards the position of the detected hand-gesture, while the third redirects it away from said position. Finally, the fourth gesture turns the light-Tracking and-redirecting system off.@en

This paper details the development of an acoustically adaptive modular system capable of enhancing Speech Clarity (C50 Clarity Index) in specific locations within a space in near real-time. The mechanical component of the system consists of quadrilateral, truncated pyramidal modules that extend or retract perpendicularly to their base. This enables said modules (1) to change in the steepness of the sides of their frustum, which changes the way incoming sound waves are deflected/reflected/diffused by the surfaces of the pyramid; and (2) to reveal or to hide the absorbent material under each module, which enables a portion of incoming sound waves to be absorbed/dissipated in a controlled manner. The present setup considers a fragmentary implementation of six modules. The behavior of these modules is determined by two steps in the computational component of the system. First, the initial position of the modules is set via a model previously generated by an evolutionary solver, which identifies the optimal extension/retraction extent of each of the six modules to select for individual configurations that collectively ascertain the highest clarity in said specific locations. Second, a simulated receiver at the location in question measures the actual clarity attained and updates the model’s database with respect to the configuration’s corresponding clarity-value. Since the nature of acoustics is not exact, if the attained measurement is lower than the model’s prediction for said location under the best module-configuration, but higher than the second-best configuration for the same location, the modules remain at the initial configuration. However, if the attained values are lower, this step reconfigures the modules to instantiate the second—or third-, fourth-, etc.—best configuration and updates the model’s database with respect to the new optimal module-configuration value. These steps repeat each time the user moves to another specific location. The objective of the system is to contribute to the intelligent and intuitive Speech Clarity regulation of an inhabited space. This contributes to its Interior Environmental Quality, which promotes well-being and quality of life.@en

This paper presents an adaptive rainwater-harvesting (RWH) system based on a rainwater-collecting unit that (1) ascertains baseline water-quality in its collected rainwater via Ph- and turbidity sensors, and (2) redistributes it to designated toilet-tanks and/or irrigation points. Each unit is integrated with an XBee S2B antenna to enable cost-effective and energy-efficient mesh capabilities for inter-unit communication when two or more units conform the system. Moreover, each unit is also an Internet-of-Things (IoT) device that transmits water-tank levels and sensor-data to a local supervising microcontroller (MCU) via Open Sound Control (OSC). This MCU is, in turn, capable of communication with a cloud-based data plotting / storing and remote-control platform - viz., Adafruit IO - via Message Queueing Telemetry Transport (MQTT). The interface with Adafruit IO enables a remote administrator (a) to monitor water-tank levels and sensor readings, and (b) to execute manual overrides in the system - for example, any or all of the units may be shut-down remotely. When only one unit conforms the system, its water-tank services the toilet-tanks and/or irrigation points connected to the unit. When two or more units conform the system, their water-tank outputs are physically linked, enabling any unit to contribute to the servicing of a variety of connected toilet-tanks and/or irrigation points. In both single or multi-unit configurations, water redistribution is impartial to any end-point at initialization, yet over time the system identifies which end-point(s) require(s) water with a higher frequency and selectively prioritizes servicing to it/them to guarantee prompt refill / supply. The present work is part of ongoing developments of features and services that attempt to imbue the builtenvironment with intelligence via Information and Communication Technologies (ICTs).@en