Forthcoming articles

 


International Journal of Humanitarian Technology

 

These articles have been peer-reviewed and accepted for publication in IJHT, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.

 

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International Journal of Humanitarian Technology (3 papers in press)

 

Regular Issues

 

  • Internet of Things (IoT) Protocols - A Survey   Order a copy of this article
    by Venetis Kanakaris, George Papakostas 
    Abstract: Several IoT protocols have been introduced to provide an efficient communication for resource-constrained applications. However, their performance is not as yet well understood. While developers employ existing technologies to build the IoT, research groups are working on adapting protocols to the IoT in order to optimize communications. To address this issue, we evaluated and compared several communication protocols, namely, MQTT, SMQTT, AMQP, CoAP, XMPP, DDS, RESTful and WebSocket. and we discuss their suitability of the IoT protocols by considering architecture, security, message techniques and QoS aspects. Lastly, we provide our conclusions for the IoT communication protocols according to the study that we have conducted.
    Keywords: Internet of Things (IoT); Application Layer Protocols; Request/Response; Publish/Subscribe.

  • Use of mHealth for Cardiovascular Disease in Low- and Middle-Income Countries with Low Peace: Systematic Review and Recommendations   Order a copy of this article
    by Cynthia Williams, Yara Asi 
    Abstract: Background: Cardiovascular disease (CVD) is the leading cause of death globally, with a disproportionately high rate in low- and middle-income countries (LMIC). Humanitarian agencies should seek innovative methods to alleviate CVD. The goal of this paper is to review evidence on the effectiveness of mHealth as a means for CVD care in fragile environments. Methods: A systematic method using PRISMA standards was conducted using three bibliographic databases. Descriptive analysis was applied, and a quality assessment was conducted using the Cochrane Risk of Bias Tool, Cochrane Qualitative Appraisal Tool, and Newcastle-Ottawa Quality Assessment. Results: The databases yielded 2,732 citations after duplicates were removed, with 111 suitable for detailed screening based on our criteria. Six met the inclusion criteria: three RCT, two qualitative studies and one cohort study.rnConclusions: There is potential to include mHealth as an adjunct to CVD care and a viable tool for providers and community health workers.rn
    Keywords: mHealth; Mobile Health; Cardiovascular disease; LMIC; Peace; Non-Communicable Diseases.

  • A decentralised framework for efficient storage and processing of big data using HDFS and IPFS   Order a copy of this article
    by Franklin John, Suji Gopinath, Elizabeth Sherly 
    Abstract: Big data revolution emerged with greater opportunities as well as challenges. Some of the major challenges include capturing, storing, transferring, analyzing, processing and updating these large and complex data sets. Traditional data handling techniques cannot manage this fast growing data. Apache Hadoop is one of the best technologies which can address the challenges involved in big data handling. Hadoop is a centralized, distributed data storage model. InterPlanetary File System (IPFS) is an emerging technology which can provide a decentralized distributed storage. By integrating both these technologies we can create a better framework for the distributed storage and processing of big data. In the proposed work we formulated a model for big data placement, replication and processing by combining the features of Hadoop and IPFS. Hadoop Distributed File System and IPFS jointly handle the data placement and replication tasks and the programming framework MapReduce in Hadoop handle the data processing task. The experimental result shows that the proposed framework can achieve cost-effective storage as well as faster processing of big data.
    Keywords: Big Data Management; Cloud Computing; HDFS; IPFS; Erasure coding.