Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (2)

Search Parameters:
Authors = Jurairat Phuttharak ORCID = 0000-0003-1785-4646

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
20 pages, 5766 KiB  
Article
An Event-Driven Architectural Model for Integrating Heterogeneous Data and Developing Smart City Applications
by Jurairat Phuttharak and Seng W. Loke
J. Sens. Actuator Netw. 2023, 12(1), 12; https://doi.org/10.3390/jsan12010012 - 1 Feb 2023
Cited by 7 | Viewed by 6667
Abstract
Currently, many governments are gearing up to promote the development of smart cities in their countries. A smart city is an urban area using different types of sensors to collect data, which will then be used to manage assets and resources efficiently. Through [...] Read more.
Currently, many governments are gearing up to promote the development of smart cities in their countries. A smart city is an urban area using different types of sensors to collect data, which will then be used to manage assets and resources efficiently. Through smart technology, the quality of living and performance of urban services are enhanced. Recent works addressed a set of platforms aimed to support the development of smart city applications. It seems that most of them involved dealing with collecting, managing, analyzing, and correlating data to extract new information useful to a city, but they do not integrate a diversified set of services and react to events on the fly. Moreover, the application development facilities provided by them seem to be limited and might even increase the complexity of this task. We propose an event-based architecture with components that meet important requirements for smart city platforms, supporting increased demand for scalability, flexibility, and heterogeneity in event processing. We implement such architecture and data representation models, handling different data formats, and supporting a semantics-based data model. Finally, we discuss the effectiveness of a S mart Event-based Middleware (SEMi) and present empirical results regarding a performance evaluation of SEMi. Full article
(This article belongs to the Section Network Services and Applications)
Show Figures

Figure 1

30 pages, 4208 KiB  
Article
Iterative Spatial Crowdsourcing in Peer-to-Peer Opportunistic Networks
by Jurairat Phuttharak and Seng W. Loke
Electronics 2020, 9(7), 1085; https://doi.org/10.3390/electronics9071085 - 2 Jul 2020
Viewed by 2720
Abstract
Spatial crowdsourcing is a potentially powerful method for incorporating human wisdom into mobile computations to solve problems while exploiting the advantages of mobility and context-awareness. This paper proposes and investigates task assignments and recruitment in iterative spatial crowdsourcing processes to find regions of [...] Read more.
Spatial crowdsourcing is a potentially powerful method for incorporating human wisdom into mobile computations to solve problems while exploiting the advantages of mobility and context-awareness. This paper proposes and investigates task assignments and recruitment in iterative spatial crowdsourcing processes to find regions of particular interest among a collection of regions. We consider cases where associations between regions can be exploited to reduce costs and increase efficiency in crowdsourcing. We describe five approaches, incorporated into crowdsourcing algorithms, for reducing the cost (the number of queries required) and increasing the efficiency (reducing the number of rounds of querying required) in using such spatial crowdsourcing. We demonstrate the performance improvements gained using these approaches based on simulation scenarios. The findings show the interplay and relationships among our proposed approaches using a range of metrics including responses, energy consumption, costs, and time usage. These metrics are demonstrated via a range of scenarios, showing that our proposed approaches can lead to improved performance over randomly choosing regions for inquiry. Full article
(This article belongs to the Special Issue Crowdsensing for Wireless Communication and Networking)
Show Figures

Figure 1

Back to TopTop