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 Person Re-Identification Based on Attention Mechanism and Context Information Fusion

2021 ◽  
Vol 13 (3) ◽  
pp. 72
Author(s):  
Shengbo Chen ◽  
Hongchang Zhang ◽  
Zhou Lei
Keyword(s):  
Information Fusion ◽  
Irrelevant Information ◽  
Features Extraction ◽  
Attention Mechanism ◽  
Cross Entropy ◽  
Context Information ◽  
Feature Map ◽  
High Level ◽  
Surveillance Analysis ◽  
High Level Feature

Person re-identification (ReID) plays a significant role in video surveillance analysis. In the real world, due to illumination, occlusion, and deformation, pedestrian features extraction is the key to person ReID. Considering the shortcomings of existing methods in pedestrian features extraction, a method based on attention mechanism and context information fusion is proposed. A lightweight attention module is introduced into ResNet50 backbone network equipped with a small number of network parameters, which enhance the significant characteristics of person and suppress irrelevant information. Aiming at the problem of person context information loss due to the over depth of the network, a context information fusion module is designed to sample the shallow feature map of pedestrians and cascade with the high-level feature map. In order to improve the robustness, the model is trained by combining the loss of margin sample mining with the loss function of cross entropy. Experiments are carried out on datasets Market1501 and DukeMTMC-reID, our method achieves rank-1 accuracy of 95.9% on the Market1501 dataset, and 90.1% on the DukeMTMC-reID dataset, outperforming the current mainstream method in case of only using global feature.

Conspicuous consumption of luxury experiences: an experimental investigation of status perceptions on social media

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carolin Siepmann ◽  
Lisa Carola Holthoff ◽  
Pascal Kowalczuk
Keyword(s):  
Social Media ◽  
Personal Characteristics ◽  
Conspicuous Consumption ◽  
Individual Characteristics ◽  
Luxury Goods ◽  
Content Type ◽  
The Status ◽  
Self Actualization ◽  
The Individual ◽  
High Level

Purpose As luxury goods are losing their importance for demonstrating status, wealth or power to others, individuals are searching for alternative status symbols. Recently, individuals have increasingly used conspicuous consumption and displays of experiences on social media to obtain affirmation. This study aims to analyze the effects of luxury and nonluxury experiences, as well as traditional luxury goods on status- and nonstatus-related dimensions. Design/methodology/approach After presenting the theoretical foundation, the authors conduct a study with 599 participants to compare status perceptions elicited by the conspicuous consumption of luxury goods, luxury experiences and nonluxury experiences. The authors investigate whether experiences that are visibly consumed on Instagram are replacing traditional luxury goods as the most important status symbols. Furthermore, the authors examine the effects of the content shown on nonstatus-related dimensions and analyze whether status perceptions differ between female and male social media communicators. Finally, the authors analyze how personal characteristics (self-esteem, self-actualization and materialism) influence the status perceptions of others on social media. Findings The results show that luxury goods are still the most important means of displaying status. However, especially for women, luxury experiences are also associated with a high level of social status. Thus, the results imply important gender differences in the perceptions of status- and nonstatus-related dimensions. Furthermore, the findings indicate that, in particular, the individual characteristics of self-actualization and materialism affect status perceptions depending on the posted content. Originality/value While the research has already considered some alternative forms of conspicuous consumption, little attention has been given to experiences as status symbols. However, with their growing importance as substitutes for luxury goods and the rise of social media, the desire to conspicuously consume experiences is increasing. The authors address this gap in the literature by focusing on the conspicuous display of luxury and nonluxury experiences on social media.

IoT-based Precision Agriculture Platform: A Review

2021 ◽  
Vol 9 (9) ◽  
pp. 1419-1421
Author(s):  
Rutvik Solanki
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Agricultural Sector ◽  
Disease Outbreaks ◽  
Iot Platforms ◽  
High Level ◽  
New Applications ◽  
And Control ◽  
Use Of Internet ◽  
The Internet Of Things

Abstract: Technological advancements such as the Internet of Things (IoT) and Artificial Intelligence (AI) are helping to boost the global agricultural sector as it is expected to grow by around seventy percent in the next two decades. There are sensor-based systems in place to keep track of the plants and the surrounding environment. This technology allows farmers to watch and control farm operations from afar, but it has a few limitations. For farmers, these technologies are prohibitively expensive and demand a high level of technological competence. Besides, Climate change has a significant impact on crops because increased temperatures and changes in precipitation patterns increase the likelihood of disease outbreaks, resulting in crop losses and potentially irreversible plant destruction. Because of recent advancements in IoT and Cloud Computing, new applications built on highly innovative and scalable service platforms are now being developed. The use of Internet of Things (IoT) solutions has enormous promise for improving the quality and safety of agricultural products. Precision farming's telemonitoring system relies heavily on Internet of Things (IoT) platforms; therefore, this article quickly reviews the most common IoT platforms used in precision agriculture, highlighting both their key benefits and drawbacks

From Users’ Intentions to IF-THEN Rules in the Internet of Things

2021 ◽  
Vol 39 (4) ◽  
pp. 1-33
Author(s):  
Fulvio Corno ◽  
Luigi De Russis ◽  
Alberto Monge Roffarello
Keyword(s):  
Internet Of Things ◽  
Smart Devices ◽  
The Internet ◽  
Short Term ◽  
Real World Data ◽  
Original Intention ◽  
Recommendation Accuracy ◽  
High Level ◽  
The Internet Of Things

In the Internet of Things era, users are willing to personalize the joint behavior of their connected entities, i.e., smart devices and online service, by means of trigger-action rules such as “IF the entrance Nest security camera detects a movement, THEN blink the Philips Hue lamp in the kitchen.” Unfortunately, the spread of new supported technologies makes the number of possible combinations between triggers and actions continuously growing, thus motivating the need of assisting users in discovering new rules and functionality, e.g., through recommendation techniques. To this end, we present , a semantic Conversational Search and Recommendation (CSR) system able to suggest pertinent IF-THEN rules that can be easily deployed in different contexts starting from an abstract user’s need. By exploiting a conversational agent, the user can communicate her current personalization intention by specifying a set of functionality at a high level, e.g., to decrease the temperature of a room when she left it. Stemming from this input, implements a semantic recommendation process that takes into account ( a ) the current user’s intention , ( b ) the connected entities owned by the user, and ( c ) the user’s long-term preferences revealed by her profile. If not satisfied with the suggestions, then the user can converse with the system to provide further feedback, i.e., a short-term preference , thus allowing to provide refined recommendations that better align with the original intention. We evaluate by running different offline experiments with simulated users and real-world data. First, we test the recommendation process in different configurations, and we show that recommendation accuracy and similarity with target items increase as the interaction between the algorithm and the user proceeds. Then, we compare with other similar baseline recommender systems. Results are promising and demonstrate the effectiveness of in recommending IF-THEN rules that satisfy the current personalization intention of the user.

MANAGERS CAN ALSO RESIST CHANGES — CAN WE DEAL WITH THIS? AN EXPLORATORY STUDY FROM JAPAN

2013 ◽  
Vol 21 (04) ◽  
pp. 447-493
Author(s):  
BALÁZS VASZKUN
Keyword(s):  
Traditional Values ◽  
Traditional Management ◽  
Japanese Firms ◽  
Work Routines ◽  
The Status ◽  
Major Reform ◽  
Mass Recruitment ◽  
Dominant Coalition ◽  
High Level ◽  
Shed Light

Japan is going through a transformation, yet it is difficult to judge which model should be chosen as a direction to go in with corporate reforms. Badly needed initiatives seeking to replace outdated managerial habits by new best practices in Japanese firms are being jeopardized by organizational members whose goal is to maintain the status quo — in terms of both political power and everyday work routines. Yet managerial habits and behaviours need to change if Japanese firms are to be entrepreneurial and innovative. According to institutionalism, blocking new initiatives is normal, and societal support is needed for major reform attempts. The focus of this paper is to shed light on how society in Japan is divided when it comes to large firms altering practices with which they have been traditionally managed. Our proposition is that complex, multi-element reform packages — having a potentially opposing dominant coalition, which is the case of Japan — ought to be implemented following a well-defined, prioritized listing of elements. After examining an attitude survey carried out in Japan, our findings revealed two clusters with a particularly high level of support for traditional management. Moreover, out of the two, one appeared to be extremely passive and resistant to any sort of change. In order to fight general resistance and reform outdated practices, our survey shows that Japan could move further towards a system compensating performance rather than seniority and giving more chance to women, discarding mass-recruitment, slow promotion whilst also maintaining the most deeply-rooted traditional values such as job security, paternalism or harmony in corporate life.

scholarly journals Polymer-Based Chemical Nose Systems for Optical Pattern Recognition of Gut Microbiota

2020 ◽  
Author(s):  
Shunsuke Tomita ◽  
Hiroyuki Kusada ◽  
Naoshi Kojima ◽  
Sayaka Ishihara ◽  
Koyomi Miyazaki ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Gut Microbiota ◽  
Health Management ◽  
Clinical Settings ◽  
Response Patterns ◽  
Bacterial Strains ◽  
Optical Pattern Recognition ◽  
Sensing Systems ◽  
Optical Pattern ◽  
The Status

Understanding the status of gut microbiota has been recognized as crucial in health management and disease treatment. To meet the demands of medical and biological applications where rapid evaluation of gut microbiota in limited research environment is essential, we developed new sensing systems able to readout the overall characteristics of complex microbiota. Response patterns generated by a synthetic library of 12 charged block-copolymers with aggregation-induced emission units were analyzed with pattern recognition algorithms, allowing to identify the species/phyla of 16 axenic cultures of intestinal bacterial strains. More importantly, our method clearly classified artificial models of obesity-associated gut microbiota, and further succeeded in detecting sleep disorders in mice through comparative analysis of the normal/abnormal mouse gut microbiota. Our techniques can analyze complex bacterial samples far more quickly, simply and inexpensively than common metagenome-based methods, offering a powerful and complementary tool for gut microbiome analysis for practical use, e.g., in clinical settings.

scholarly journals Transdisciplinary System of Systems Development in the Trend to X4.0

2020 ◽  
Author(s):  
John P.T. Mo ◽  
Ronald C. Beckett
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Systems Design ◽  
System Of Systems ◽  
Systems Perspective ◽  
Platform Process ◽  
Quality Water ◽  
High Level ◽  
World Environment ◽  
The Internet Of Things

Since the announcement of Industry 4.0 in 2012, multiple variants of this industry paradigm have emerged and built on the common platform of Internet of Things. Traditional engineering driven industries such as aerospace and automotive are able to align with Industry 4.0 and operate on requirements of the Internet of Things platform. Process driven industries such as water treatment and food processing are more influenced by societal perspectives and evolve into Water 4.0 or Dairy 4.0. In essence, the main outcomes of these X4.0 (where X can be any one of Quality, Water or a combination of) paradigms are facilitating communications between socio-technical systems and accumulating large amount of data. As the X4.0 paradigms are researched, defined, developed and applied, many real examples in industries have demonstrated the lack of system of systems design consideration, e.g. the issue of training together with the use of digital twin to simulate operation scenarios and faults in maintenance may lag behind events triggered in the hostile real world environment. This paper examines, from a high level system of systems perspective, how transdisciplinary engineering can incorporate data quality on the often neglected system elements of people and process while adapting applications to operate within the X4.0 paradigms.

scholarly journals Baa, Baa, Black Sheep  Have You Any Wool?  Developing the RBV  Through a Study of the  New Zealand Merino Clothing Industry

2021 ◽  
Author(s):  
◽  
Andrew Jackson
Keyword(s):  
New Zealand ◽  
Profile Analysis ◽  
Secondary Data ◽  
Structured Interview ◽  
Clothing Industry ◽  
Black Sheep ◽  
Key Characteristics ◽  
High Level ◽  
Traditional Approaches ◽  
Competitive Rivalry

<p>This thesis explores how the traditional approaches to researching the Resource-Based View (RBV) do not fully address the heterogeneity within the participants of the research. Traditional approaches assume similar levels of knowledge, prioritisation, and value (awareness) are held across the participants. This thesis proposes that this similarity may not exist for every industry. Focused on the New Zealand merino clothing industry, this research employed two studies to determine the key characteristics and perceptions of the main players in the industry. Initially an industry profile is formed from secondary data sources, which covers the 30 years since the inception of the New Zealand merino clothing industry. This profile forms the basis for the interview sample and provides comparison for interview findings. Through the use of open-ended questions and a semi-structured interview process this thesis carried out interviews with the CEOs of thirteen New Zealand based merino clothing firms from throughout New Zealand. These interviews offered the participants the opportunity to express their perspectives on the resources they deem to be most important. The outcomes of these interviews are surprising; with the results questioning more assumptions of RBV research than just the similarity of awareness. Drawing together the analysis of the industry profile and the findings of the interviews, these two studies highlight a number of key findings. Most significantly, it is apparent that the majority of the interviewees do not perceive themselves as competing, though the industry profile indicates that the industry has a high level of competitive rivalry. Additionally, the firms do not appear to be differentiating themselves from one another, with few unique approaches utilised by the interviewees in regards to product, design, and business practice. Lastly, this thesis illustrates that these differences in perception between the industry profile analysis and the interview findings could be due to the ambition and future perspectives of the CEOs.</p>

scholarly journals Development of an IoT System for Environmental Monitoring: Software

2021 ◽  
Author(s):  
Benjamin Secker
Keyword(s):  
Environmental Monitoring ◽  
Low Cost ◽  
Proof Of Concept ◽  
Embedded Devices ◽  
Data Loggers ◽  
Environmental Monitoring System ◽  
Use Of The Internet ◽  
High Level ◽  
Monitoring Software ◽  
The Internet Of Things

Use of the Internet of Things (IoT) is poised to be the next big advancement in environmental monitoring. We present the high-level software side of a proof-of-concept that demonstrates an end-to-end environmental monitoring system,<br><div>replacing Greater Wellington Regional Council’s expensive data loggers with low-cost, IoT centric embedded devices, and it’s supporting cloud platform. The proof-of-concept includes a Micropython-based software stack running on an ESP32 microcontroller. The device software includes a built-in webserver that hosts a responsive Web App for configuration of the device. Telemetry data is sent over Vodafone’s NB-IoT network and stored in Azure IoT Central, where it can be visualised and exported.</div><br>While future development is required for a production-ready system, the proof-of-concept justifies the use of modern IoT technologies for environmental monitoring. The open source nature of the project means that the knowledge gained can be re-used and modified to suit the use-cases for other organisations.

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