Radio telemetry for wireless sensing in intelligent buildings

Fully-physically crosslinked hydrogels with strain sensitivity and anti-freezing properties for wireless sensing and low temperature sensing were prepared.

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Movement syndromes of a Neotropical frugivorous bat inhabiting heterogeneous landscapes in Brazil

Movement Ecology ◽

10.1186/s40462-021-00266-6 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Patricia Kerches-Rogeri ◽

Danielle Leal Ramos ◽

Jukka Siren ◽

Beatriz de Oliveira Teles ◽

Rafael Souza Cruz Alves ◽

...

Keyword(s):

Site Fidelity ◽

Animal Movement ◽

Radio Telemetry ◽

Food Resource ◽

Movement Behavior ◽

Movement Activity ◽

Landscape Features ◽

Heterogeneous Landscapes ◽

Movement Data ◽

High Site

Abstract Background There is growing evidence that individuals within populations can vary in both habitat use and movement behavior, but it is still not clear how these two relate to each other. The aim of this study was to test if and how individual bats in a Stunira lilium population differ in their movement activity and preferences for landscape features in a correlated manner. Methods We collected data on movements of 27 individuals using radio telemetry. We fitted a heterogeneous-space diffusion model to the movement data in order to evaluate signals of movement variation among individuals. Results S. lilium individuals generally preferred open habitat with Solanum fruits, regularly switched between forest and open areas, and showed high site fidelity. Movement variation among individuals could be summarized in four movement syndromes: (1) average individuals, (2) forest specialists, (3) explorers which prefer Piper, and (4) open area specialists which prefer Solanum and Cecropia. Conclusions Individual preferences for landscape features plus food resource and movement activity were correlated, resulting in different movement syndromes. Individual variation in preferences for landscape elements and food resources highlight the importance of incorporating explicitly the interaction between landscape structure and individual heterogeneity in descriptions of animal movement.

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Use of a spatially explicit individual-based model to predict population trajectories and habitat connectivity for a reintroduced ursid

Oryx ◽

10.1017/s0030605320000447 ◽

2021 ◽

pp. 1-10

Author(s):

Desiree Andersen ◽

Yoonjung Yi ◽

Amaël Borzée ◽

Kyungmin Kim ◽

Kwang-Seon Moon ◽

...

Keyword(s):

Population Dynamics ◽

Radio Telemetry ◽

Suitable Habitat ◽

Large Carnivores ◽

Environmental Interactions ◽

Dispersal Capability ◽

The Republic ◽

Suitable Habitats ◽

Mixed Modelling ◽

Population Equilibrium

Abstract Reintroductions of large carnivore species present unique opportunities to model population dynamics as populations can be monitored from the beginning of a reintroduction. However, analysis of the population dynamics of such reintroduced populations is rare and may be limited in incorporating the complex movements and environmental interactions of large carnivores. Starting in 2004, Asiatic black bears Ursus thibetanus were reintroduced and tracked in the Republic of Korea, along with their descendants, using radio telemetry, yielding 33,924 tracking points over 12 years. Along with information about habitat use, landscape, and resource availability, we estimated the population equilibrium and dispersal capability of the reintroduced population. We used a mixed modelling approach to determine suitable habitat areas, population equilibria for three different resources-based scenarios, and least-cost pathways (i.e. corridors) for dispersal. Our population simulations provided a mean population equilibrium of 64 individuals at the original reintroduction site and a potential maximum of 1,438 individuals in the country. The simulation showed that the bear population will disperse to nearby mountainous areas, but a second reintroduction will be required to fully restore U. thibetanus. Northern suitable habitats are currently disconnected and natural re-population is unlikely to happen unless supported. Our methodologies and findings are also relevant for determining the outcome and trajectories of reintroduced populations of other large carnivores.

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Deep AI Enabled Ubiquitous Wireless Sensing

ACM Computing Surveys ◽

10.1145/3436729 ◽

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.

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An Energy-efficient Street Lighting Approach Based on Traffic Parameters Measured by Wireless Sensing Technology

IEEE Sensors Journal ◽

10.1109/jsen.2021.3089208 ◽

2021 ◽

pp. 1-1

Author(s):

Yuxi Jiang ◽

Yinghong Shuai ◽

Xiaoliang He ◽

Xing Wen ◽

Liangliang Lou

Keyword(s):

Energy Efficient ◽

Wireless Sensing ◽

Street Lighting ◽

Sensing Technology

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