Inferring Human Activity Recognition with Ambient Sound on Wireless Sensor Nodes

Salomons, Etto L.; Havinga, Paul J.M.; Leeuwen, Henk van

doi:10.3390/s16101586

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…However, due to the affordable and low energy-consumption character typical of WSN nodes built on affordable platforms (e.g., Arduino, Raspberry Pi, etc. ), computational processing with respect to feature extraction has been considerably limited [197]. To overcome this limitation, the present implementation is capable of instantiating ad hoc clusters consisting of a variety of high-performance nodes.…”

Section: St Development: Non-proprietary Human Activity Recognition (...mentioning

confidence: 99%

The Intelligent Built-Environment as Cyber-Physical System

Liu Cheng

2024

Architecture and the Built Environment

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This thesis presents an alternative approach to intelligence in the built-environment, departing from the two established yet divergent branches in the discourse: the Technical, centered around Information and Communication Technologies (ICTs), and represented by Ambient Intelligence (AmI) and Ambient Assisted Living (AAL); and the Architectural, centered around architectural / spatial experiences and considerations, and represented by Interactive Architecture and Adaptive Architecture. The promise of both AmI/AAL and IA/AA is constrained by rigid and increasingly outdated assumptions in their approaches—i.e., AmI’s / AAL’s approach to the built-environment, and IA’s / AA’s approach to ICTs. Moreover, it is impossible to combine them to yield a cohesive system due to disparity in their typical Technology Readiness Levels. That is, the sophistication of a system depends on that of its mutually complementing subsystems; and two or more subsystems may not mutually complement, sustain, and/or support one another if their levels of development do not correspond. Consequently, the presented alternative conceives the intelligent built-environment as a Cyber- Physical System. Under this approach, ICTs and Architectural considerations in conjunction instantiate intelligence fundamentally. The presented approach’s promise is illustrated via its application to a constrained use-case focused on the elderly. Twelve proof-of-concept demonstrators are developed based on key parameters pertaining to Indoor Environmental Quality and Quality of Life. While each demonstrator is presented as a discrete proof-of-concept, all build on the same core System Architecture and technological ecosystem, and are intended to be viewed as a collection of systems and services expressed within a same hypothetical environment.

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Section: St Development: Non-proprietary Human Activity Recognition (...mentioning

confidence: 99%

The Intelligent Built-Environment as Cyber-Physical System

Liu Cheng

2024

Architecture and the Built Environment

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“…HAR, as one such application, has successfully exploited classifiers in the last five years (see, for example, (Xiao and Lu 2015;Villa et al 2012;Andreu and Angelov 2013). However, due to the cost-effective and low energy-consumption character typical of WSAN nodes, computational processing with respect to feature extraction has been considerably limited (Salomons et al 2016). To overcome this limitation, the present implementation is capable of instantiating ad hoc clusters consisting of a variety of high-performance nodes.…”

Section: Machine Learning 10mentioning

confidence: 99%

Visions of Process—Swarm Intelligence and Swarm Robotics in Architectural Design and Construction

Vehlken

2018

Springer Series in Adaptive Environments

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Robotic Building implies both physically built robotic environments and robotically supported building processes. Physically built robotic environments consist of reconfigurable, adaptive systems incorporating sensor-actuator mechanisms that enable buildings to interact with their users and surroundings in real-time. These robotic environments require Design-to-Production and-Operation (D2P&O) chains that may be (partially or completely) robotically driven. This chapter describes previous work aiming to integrate D2RP&O processes by linking performance-driven design with robotic production and user-driven building operation. 5.1 Introduction While architecture and architectural production are increasingly incorporating aspects of non-human agency employing data, information, and knowledge contained within the (worldwide) network connecting electronic devices, the question is not whether but how robotic systems can be incorporated into building processes and buildings (Oosterhuis and Bier 2013). This chapter aims to answer this question by reflecting on the achievements of the Robotic Building (RB) team at Technical University Delft (TU Delft) and by identifying future steps. The focus is on an architecture that is robotically enabled to interact with its users and surroundings in real-time and the corresponding Design-to-Production and-Operation (D2P&O) processes that are (in part or as whole) robotically driven. Such modes of production and operation involve agency of both humans and non-humans. Thus agency is not The original version of the book was revised: Open access text has been updated in FM, Chapter

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“…HAR, as one such application, has successfully exploited said classifiers in the last five years (see, for example, [13][14][15]). However, due to the cost-effective and low energy-consumption character typical of WSAN nodes, computational processing with respect to feature extraction has been considerably limited [16]. To overcome this limitation, the present implementation is capable of instantiating ad hoc clusters consisting of a variety of high-performance nodes.…”

Section: Development Of a Cost-effective Human Activity Recognition (mentioning

confidence: 99%

A High-Resolution Intelligence Implementation based on Design-to-Robotic-Production and -Operation Strategies

Cheng¹,

Bier²,

Latorre³

et al. 2017

Proceedings of the International Symposium on Automation and Robotics in Construction (IAARC)

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-This paper presents an initial proof-of-concept implementation of a comprehensively intelligent built-environment based on mutually informing Design-to-Robotic-Production and -Operation (D2RP&O) strategies and methods developed at Delft University of Technology (TUD). In this implementation, D2RP is expressed via deliberately differentiated and function-specialized components, while D2RO expressions subsume an extended Ambient Intelligence (AmI) enabled by a CyberPhysical System (CPS). This CPS, in turn, is built on a heterogeneous, scalable, self-healing, and partially meshed Wireless Sensor and Actuator Network (WSAN) whose nodes may be clustered dynamically ad hoc to respond to varying computational needs.Two principal and innovative functionalities are demonstrated in this implementation: (1) costeffective yet robust Human Activity Recognition (HAR) via Support Vector Machine (SVM) and kNearest Neighbor (k-NN) classification models, and (2) appropriate corresponding reactions that promote the occupant's spatial experience and wellbeing via continuous regulation of illumination with respect to colors and intensities to correspond to engaged activities.The present implementation attempts to provide a fundamentally different approach to intelligent built-environments, and to promote a highly sophisticated alternative to existing intelligent solutions whose disconnection between architectural considerations and computational services limits their operational scope and impact.

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Inferring Human Activity Recognition with Ambient Sound on Wireless Sensor Nodes

Cited by 8 publications

References 12 publications

The Intelligent Built-Environment as Cyber-Physical System

The Intelligent Built-Environment as Cyber-Physical System

Visions of Process—Swarm Intelligence and Swarm Robotics in Architectural Design and Construction

A High-Resolution Intelligence Implementation based on Design-to-Robotic-Production and -Operation Strategies

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