Mobile merchandise evaluation service using novel information retrieval and image recognition technology

Lo, Chi-Chun; Kuo, Ting-Huan; Kung, H. T.; Kao, Hsiang-Ting; Chen, Chi‐Hua; Wu, Che-I; Cheng, Ding-Yuan

doi:10.1016/j.comcom.2010.03.033

Cited by 10 publications

(5 citation statements)

References 13 publications

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“…For example, the Interworking Proxy Entity (IPE) was designed to establish the connection of oneM2M, AllJoyn, OCF, and Lightweight M2M in oneM2M's Release 2 [1]. Some communication techniques have been proposed to collect the sensing data and control the devices via different IoT standards and specifications for the applications of agriculture [17][18][19], energy [20,21], enterprise [22,23], finance [24,25], healthcare [26,27], industry [28,29], public services [30,31], residency [32,33], retail [34,35], and transportation [36][37][38][39][40]. Therefore, the aim of this special issue is to introduce to the readers a number of papers on various aspects of IoT applications and techniques.…”

Section: Introductionmentioning

confidence: 99%

Introduction to the Special Issue: Applications of Internet of Things

et al. 2018

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This editorial introduces the special issue, entitled “Applications of Internet of Things”, of Symmetry. The topics covered in this issue fall under four main parts: (I) communication techniques and applications, (II) data science techniques and applications, (III) smart transportation, and (IV) smart homes. Four papers on sensing techniques and applications are included as follows: (1) “Reliability of improved cooperative communication over wireless sensor networks”, by Chen et al.; (2) “User classification in crowdsourcing-based cooperative spectrum sensing”, by Zhai and Wang; (3) “IoT’s tiny steps towards 5G: Telco’s perspective”, by Cero et al.; and (4) “An Internet of things area coverage analyzer (ITHACA) for complex topographical scenarios”, by Parada et al. One paper on data science techniques and applications is as follows: “Internet of things: a scientometric review”, by Ruiz-Rosero et al. Two papers on smart transportation are as follows: (1) “An Internet of things approach for extracting featured data using an AIS database: an application based on the viewpoint of connected ships”, by He et al.; and (2) “The development of key technologies in applications of vessels connected to the Internet”, by Tian et al. Two papers on smart home are as follows: (1) “A novel approach based on time cluster for activity recognition of daily living in smart homes”, by Liu et al.; and (2) “IoT-based image recognition system for smart home-delivered meal services”, by Tseng et al.

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Section: Introductionmentioning

confidence: 99%

Introduction to the Special Issue: Applications of Internet of Things

et al. 2018

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“…For sensor and networking layers, the rise of mobile technology advancements [12][13][14][15] (e.g., wireless sensor networking, Wi-Fi, Bluetooth, smart mobile device, and Long Term Evolution (LTE)) has led to a new wave of machine-to-machine (M2M), machine-to-human (M2H), human-to-human (H2H), and human-to-machine (H2M) communications [16][17][18][19][20]. For the application layer, several IoT applications, which include energy [21,22], enterprise [23,24], healthcare [25,26], public services [27,28], residency [29,30], retail [31,32], and transportation [33,34], have been designed and implemented to detect environmental changes and send instant updates to a cloud computing server farm via mobile communications and middleware for big geo-data analyzes [35,36]. For instance, on-board units in cars can instantly detect and share information about the geolocation of the car, speed, following distance, and gaps with other neighboring cars [37][38][39][40].…”

Section: Introductionmentioning

confidence: 99%

Applications of Internet of Things

Chen

2018

IJGI

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This editorial introduces the special issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITS), (II) location-based services (LBS), and (III) sensing techniques and applications. Three papers on ITS are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBS are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al.

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“…Furthermore, the mean absolute percentage error (MAPE) was considered to define the accuracy of the forecasted travel time as . The k-fold cross-validation method [3] was adopted to evaluate the average accuracy of the forecasted travel time for each road segment between collection points. For instance, the historical data during April was adopted as a testing dataset, and the remaining data (i.e., the historical data from May to October) was used as a training dataset in the first round.…”

Section: Implementation and Evaluationmentioning

confidence: 99%

“…In recent years, the improvement of cloud computing and mobile computing techniques has led to the availability of a variety of mobile applications in the app store [1][2][3]. Furthermore, several mobile applications of intelligent transportation systems (ITS), which include bus apps [4], public bicycle systems [5], mass rapid transit systems [6], and railway apps [7], have been developed and implemented to provide convenient transport services for residents.…”

Section: Introductionmentioning

confidence: 99%

The Design and Implementation of a Garbage Truck Fleet Management System

Chen

Yang

Chang

et al. 2016

SAJIE

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In recent years, the improvement of cloud computing and mobile computing techniques has led to the availability of a variety of mobile applications ('apps') in the app store. For instance, a garbage truck app that can provide the immediate location of a garbage truck, the location of collection points, and forecasted arrival times of garbage trucks would be useful for mobile users. Since the power consumption of apps on mobile devices if of concern to mobile users, an optimised power-saving mechanism for updating messages, which is based on location information, for a proposed garbage truck fleet management system (GTFMS) is proposed and implemented in this paper. The GTFMS is a threecomponent system that includes the on-board units on garbage trucks, a fleet management system, and a garbage truck app. In this study, an arrival time forecasting method is designed and implemented in the fleet management system, so that the garbage truck app can retrieve the forecasted arrival time via web services. A message updating event is then triggered that reports the location of garbage truck and the forecasted arrival time. In experiments conducted on case studies, the results showed that the mean accuracy of predicted arrival time by the proposed method is about 81.45 per cent. As for power consumption, the cost of traditional mobile apps is 2,880 times that of the mechanism proposed in this study. Consequently, the GTFMS can provide the precise forecasted arrival time of garbage trucks to mobile users, while consuming less power. OPSOMMINGDie verbetering van wolkverwerking en mobiele verwerkingstegnieke het gelei tot die beskikbaarheid van 'n groot verskeidenheid mobiele toepassings. 'n Voorbeeld hiervan is 'n toepassing wat die onmiddellike ligging van 'n vullistrok, die ligging van vullis versamelpunte en die voorspelde aankomstye van die vullistrokke aan die gebruiker verskaf. Die energieverbruik van die toepassings is ook van belang en 'n geoptimeerde energiebesparingsmeganisme vir die opdateer van boodskappe (wat inligting rakende die vullistrok se ligging bevat) word in hierdie artikel ontwerp en geïmplementeer. 'n Opdateringsboodskap rapporteer die vullistrok se ligging en voorspelde aankomstyd. Gevallestudies toon dat die gemiddelde akkuraatheid van die voorspelde aankomstyd 81.45% is. Die energieverbruik van die toepassing is 2880 keer minder as dié van 'n tradisionele mobiele toepassing. Gevolglik kan die voorgestelde vullistrokvlootbestuurstelsel 'n baie akkurate aankomstyd voorspelling aan gebruikers gee terwyl dit min energie verbuik. 33 INTRODUCTIONIn recent years, the improvement of cloud computing and mobile computing techniques has led to the availability of a variety of mobile applications in the app store [1][2][3]. Furthermore, several mobile applications of intelligent transportation systems (ITS), which include bus apps [4], public bicycle systems [5], mass rapid transit systems [6], and railway apps [7], have been developed and implemented to provide convenient transport services for resid...

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Mobile merchandise evaluation service using novel information retrieval and image recognition technology

Cited by 10 publications

References 13 publications

Introduction to the Special Issue: Applications of Internet of Things

Introduction to the Special Issue: Applications of Internet of Things

Applications of Internet of Things

The Design and Implementation of a Garbage Truck Fleet Management System

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