Experience-Sharing System Using Ubiquitous Sensing Environments

2005 ◽  
pp. 90-103 ◽  
Author(s):  
Megumu Tsuchikawa ◽  
Shoichiro Iwasawa ◽  
Sadanori Ito ◽  
Atsushi Nakahara ◽  
Yasuyuki Sumi ◽  
...  
Keyword(s):  
Ubiquitous Sensing

Deep AI Enabled Ubiquitous Wireless Sensing

2021 ◽  
Vol 54 (2) ◽  
pp. 1-35
Author(s):  
Chenning Li ◽  
Zhichao Cao ◽  
Yunhao Liu
Keyword(s):  
Great Success ◽  
Wireless Sensing ◽  
Ubiquitous Sensing ◽  
Sensing Systems ◽  
The Status ◽  
Sensing Model ◽  
High Level ◽  
Traditional Approaches ◽  
The Internet Of Things ◽  
High Level Feature

With the development of the Internet of Things (IoT), many kinds of wireless signals (e.g., Wi-Fi, LoRa, RFID) are filling our living and working spaces nowadays. Beyond communication, wireless signals can sense the status of surrounding objects, known as wireless sensing , with their reflection, scattering, and refraction while propagating in space. In the last decade, many sophisticated wireless sensing techniques and systems were widely studied for various applications (e.g., gesture recognition, localization, and object imaging). Recently, deep Artificial Intelligence (AI), also known as Deep Learning (DL), has shown great success in computer vision. And some works have initially proved that deep AI can benefit wireless sensing as well, leading to a brand-new step toward ubiquitous sensing. In this survey, we focus on the evolution of wireless sensing enhanced by deep AI techniques. We first present a general workflow of Wireless Sensing Systems (WSSs) which consists of signal pre-processing, high-level feature, and sensing model formulation. For each module, existing deep AI-based techniques are summarized, further compared with traditional approaches. Then, we provide a view of issues and challenges induced by combining deep AI and wireless sensing together. Finally, we discuss the future trends of deep AI to enable ubiquitous wireless sensing.

scholarly journals Introducing the Special Issue on “Ubiquitous Sensing for Smart Health Monitoring”

Information ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 74
Author(s):  
Yusuf A. Bhagat
Keyword(s):  
Health Monitoring ◽  
Special Issue ◽  
Ubiquitous Sensing ◽  
Smart Health

Sensors continue to pervade our surroundings in undiminished ways [...]

SonicFace

2021 ◽  
Vol 5 (4) ◽  
pp. 1-33
Author(s):  
Yang Gao ◽  
Yincheng Jin ◽  
Seokmin Choi ◽  
Jiyang Li ◽  
Junjie Pan ◽  
...  
Keyword(s):  
Facial Expressions ◽  
Microphone Array ◽  
Wearable Sensors ◽  
Real Life ◽  
Privacy Concerns ◽  
Fine Grained ◽  
Recognition Of Facial Expressions ◽  
Ubiquitous Sensing ◽  
Contact Free

Accurate recognition of facial expressions and emotional gestures is promising to understand the audience's feedback and engagement on the entertainment content. Existing methods are primarily based on various cameras or wearable sensors, which either raise privacy concerns or demand extra devices. To this aim, we propose a novel ubiquitous sensing system based on the commodity microphone array --- SonicFace, which provides an accessible, unobtrusive, contact-free, and privacy-preserving solution to monitor the user's emotional expressions continuously without playing hearable sound. SonicFace utilizes a pair of speaker and microphone array to recognize various fine-grained facial expressions and emotional hand gestures by emitted ultrasound and received echoes. Based on a set of experimental evaluations, the accuracy of recognizing 6 common facial expressions and 4 emotional gestures can reach around 80%. Besides, the extensive system evaluations with distinct configurations and an extended real-life case study have demonstrated the robustness and generalizability of the proposed SonicFace system.

Evaluation of Strategic Opportunities and Resulting Business Models for SMEs

2020 ◽  
pp. 148-186 ◽  
Author(s):  
Izabella V. Lokshina ◽  
Cees J. M. Lanting ◽  
Barbara Durkin
Keyword(s):  
Business Models ◽  
Management Practices ◽  
Environmental Indicators ◽  
Third Party ◽  
Easy Access ◽  
The Internet ◽  
Knowledge Based ◽  
Ubiquitous Sensing ◽  
Provision Of Services ◽  
And Control

This chapter focuses on ubiquitous sensing devices, enabled by Wireless Sensor Network (WSN) technologies, that cut across every area of modern day living, affecting individuals and businesses and offering the ability to measure and understand environmental indicators. The proliferation of these devices in a communicating-actuating network creates the internet of things (IoT). The IoT provides the tools to establish a major global data-driven ecosystem with its emphasis on Big Data. Currently, business models may focus on the provision of services, i.e., the internet of services (IoS). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support creating revenue and value for different types of customers. This chapter contributes to the literature by considering, innovatively, knowledge-based management practices, strategic opportunities and resulting business models for third-party data analysis services.

scholarly journals Multi-Level Elasticity for Wide-Area Data Streaming Systems: A Reinforcement Learning Approach

Algorithms ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 134 ◽  
Author(s):  
Gabriele Russo Russo ◽  
Matteo Nardelli ◽  
Valeria Cardellini ◽  
Francesco Lo Presti
Keyword(s):  
Reinforcement Learning ◽  
High Volume ◽  
Wide Area ◽  
Data Streaming ◽  
Application Performance ◽  
Ubiquitous Sensing ◽  
Self Adaptation ◽  
Adaptation Policies ◽  
Multi Level ◽  
Dsp Applications

The capability of efficiently processing the data streams emitted by nowadays ubiquitous sensing devices enables the development of new intelligent services. Data Stream Processing (DSP) applications allow for processing huge volumes of data in near real-time. To keep up with the high volume and velocity of data, these applications can elastically scale their execution on multiple computing resources to process the incoming data flow in parallel. Being that data sources and consumers are usually located at the network edges, nowadays the presence of geo-distributed computing resources represents an attractive environment for DSP. However, controlling the applications and the processing infrastructure in such wide-area environments represents a significant challenge. In this paper, we present a hierarchical solution for the autonomous control of elastic DSP applications and infrastructures. It consists of a two-layered hierarchical solution, where centralized components coordinate subordinated distributed managers, which, in turn, locally control the elastic adaptation of the application components and deployment regions. Exploiting this framework, we design several self-adaptation policies, including reinforcement learning based solutions. We show the benefits of the presented self-adaptation policies with respect to static provisioning solutions, and discuss the strengths of reinforcement learning based approaches, which learn from experience how to optimize the application performance and resource allocation.

Future Trends in Sensed-Information Technology and Sensor Systems Research

2002 ◽  
Author(s):  
Alison Flatau ◽  
Usha Varshney ◽  
Peter Chang
Keyword(s):  
Information Technology ◽  
Information Technologies ◽  
New Technologies ◽  
Sensor System ◽  
Full Potential ◽  
Sensor Systems ◽  
Research Issues ◽  
Ubiquitous Sensing ◽  
Systems Research ◽  
Research And Education

Advances in MEMs, wireless, information technology and other enabling technologies are leading to new sensor system functionality and access to more accurate data and information than heretofore realizable. These advances are crucial for realizing the full potential of the on-going transition from data-poor to data-rich and information-poor to information-rich science and engineering practices. With decreases in size and cost of sensors resulting from advances in microsystem technologies, ubiquitous sensing is becoming both physically realizable and economically feasible. New developments in sensed-information technologies offer the promise of novel insights and advances in areas that have previously lacked the technology base for acquiring high resolution and highly specific assessments of state (biologic, chemical, physical, optical, etc.). Increased research and education are needed in new technologies addressing research issues relating to new hardware and software for efficient acquisition of data and information, and in new decision and control theory as tools for managing and using available data and information. New sensor system functionality will be realized through countless different design concepts. This paper examines some of the needs, opportunities, and trends for research and education in the area of sensed-information and sensor systems research.

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