No abstract

Purpose: This paper reports on the development of a low-power fire potential monitoring system for densely populated housing based on IoT Study design: This system consists of sensors integrated with a microcontroller and a Wi-Fi module that can provide data in real-time and can be accessed remotely. In addition, this system has also been simulated to analyze environmental conditions as notification data sent using cloud messenger. The grouping of potential fire hazards based on the legibility of physical parameter values is also displayed. Findings: In performance measurement, the data loss of this system is less than 1% of the total data every day. Value: It shows that this system is feasible and applied more broadly to anticipate fires in densely populated areas.

Background: As the standard for the exchange of data over the World Wide Web, it is important to ensure that the eXtensible Markup Language (XML) database is capable of supporting not only efficient query processing but also capable of enduring frequent data update operations over the dynamic changes of Web content. Most of the existing XML annotation is based on a labeling scheme to identify each hierarchical position of the XML nodes. This computation is costly as any updates will cause the whole XML tree to be re-labelled. This impact can be observed on large datasets. Therefore, a robust labeling scheme that avoids re-labeling is crucial. Method: Here, we present ORD-GAP (named after Order Gap), a robust and persistent XML labeling scheme that supports dynamic updates. ORD-GAP assigns unique identifiers with gaps in-between XML nodes, which could easily identify the level, Parent-Child (P-C), Ancestor-Descendant (A-D) and sibling relationship. ORD-GAP adopts the OrdPath labeling scheme for any future insertion. Results: We demonstrate that ORD-GAP is robust enough for dynamic updates, and have implemented it in three use cases: (i) left-most, (ii) in-between and (iii) right-most insertion. Experimental evaluations on DBLP dataset demonstrated that ORD-GAP outperformed existing approaches such as ORDPath and ME Labeling concerning database storage size, data loading time and query retrieval. On average, ORD-GAP has the best storing and query retrieval time. Conclusion: The main contributions of this paper are: (i) A robust labeling scheme named ORD-GAP that assigns certain gap between each node to support future insertion, and (ii) An efficient mapping scheme, which built upon ORD-GAP labeling scheme to transform XML into RDB effectively.

eXtensible Markup Language (XML), in its semi-structured format has been employed for the data exchange purpose over the Internet due to its expressivity, flexibility, and capability to accommodate both structured and unstructured data. Due to the vast amount of data being transacted and updated frequently, it is essential to have a solution that can efficiently store and query the data. Hence, a robust and persistent labeling scheme that can sustain the need to relabeling the entire document is desirable. Relational Database (RDB) has emerged since the 1970s and has been widely used as back-end storage in most industries. Since XML and RDB are in different formats, an efficient mapping technique is required. Several labeling and mapping schemes have been proposed, yet, there is no comparison of the performance of these schemes implemented in the RDB storage. In this paper, we first review the dynamic labeling schemes such as ORDPath, ME Labeling, and ORD-GAP in addressing these two needs. Secondly, the XML annotated labeling schemes are transformed into RDB storage. Finally, the performance evaluations are carried out to determine which labeling scheme is more robust and efficient to support storage and query retrieval.

<span>eXtensible Markup Language (XML) has been widely used as the standard for data exchange standard over the Internet. With the fast growing rate of data, especially with high updates, it is crucial to ensure that the XML is able to cope with frequent changes with very least effect on the existing structure. Therefore, in this paper, we investigate on the existing labeling schemes and mapping approaches to gauge a better understanding in terms of the robustness of the labeling schemes and the importance of the mapping schemes. Next, we propose ORD-GAP labeling schemes to identify the structural relationship among XML nodes and yet, it is persistent to re-labeling when new nodes are inserted. Subsequently, a mapping scheme is proposed to transform XML into Relational Database (RDB). Preliminary experimental evaluation demonstrated that the proposed approach achieve 66% better as compared to ORDPATH, and 56% better as compared to ME labeling in terms of data loading time. </span>