An optimization approach to capacity planning of aggregators and resource provisioning in cloud providers for meteorological sensor network

Sandar, Nay Myo; Myint, Lin Min Min; Chaisiri, Sivadon

doi:10.1109/jcsse.2015.7219795

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…Based on our findings, among the Cloud platform providers, Amazon [39,43,96] and IBM [82,96] have the highest utility in healthcare systems. Many of the relevant studies have not yet published any information about Cloud platform providers; therefore, it is necessary to conduct further research to examine the advantages and disadvantages in this field.…”

Section: Cloud Platforms (Crq7)mentioning

confidence: 72%

“…The majority of studies related to CIoT were published in non-healthcare fields such as smart cities [100,101], transportation [102], traffic control [103], agriculture [43], smart environments [82], and smart homes [84]. In the healthcare field, the IoT and Cloud have been considered two separate technologies, and few studies have focused on their integration.…”

Section: Main Domains Of the Cloud-based Iot (Crq3)mentioning

confidence: 99%

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Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review

Gholamhosseini

Behmanesh

Nasiri

et al. 2023

Front Health Inform

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Introduction: The Internet of Things (IoT) and Cloud computing are two recent technological advances whose potential have not been realized in a range of industries. These technologies have been used in healthcare systems to improve their performance. In this regard, the IoT generates a large amount of data; also, cloud computing is a viable option for data storage and complex computing. The purpose of this study is to identify and categorize various aspects of CIoT-based healthcare in terms of main application domains, sensors, wireless communication technologies, messaging protocols, cloud platforms, and artificial intelligence (AI) algorithms.Material and Methods: We conducted a literature systematic review and reported according to the PRISMA guideline. PubMed, IEEE, Scopus, and Web of Science were searched using the related keywords and their synonyms. Two independent authors reviewed the papers' eligibility according to the defined inclusion and exclusion criteria.Results: Of the 2,118 papers retrieved, 61 were eventually selected in the study. Results of the present study revealed that the majority of CIoT research works were applied to patient monitoring systems and cardiovascular patient monitoring systems using Amazon and IBM dominating Cloud platforms. In addition, the most widely used communication technologies for CIoT in healthcare are cellular networks (3G and 4G), Wi-Fi, and Bluetooth. Cardiovascular, environmental, and position sensors are also the most common types of sensors used in healthcare CIoT applications. Among the Cloud platform providers, Amazon and IBM have the highest utility in healthcare systems. The majority of the included studies used Cloud-based AI algorithms to diagnose, classify, and predict diseases.Conclusion: The integration of the Cloud into the IoT can support healthcare systems in terms of processing power, storage capacity, security, privacy, performance, reliability, and scalability. We suggest researchers conduct experimental studies to evaluate the effectiveness of the CIoT approach in healthcare applications.

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Section: Cloud Platforms (Crq7)mentioning

confidence: 72%

Section: Main Domains Of the Cloud-based Iot (Crq3)mentioning

confidence: 99%

Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review

Gholamhosseini

Behmanesh

Nasiri

et al. 2023

Front Health Inform

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“…A well-known method within this approach is the weighted sum method, as described by Deb (2014). Examples of illustrative research that utilize the weighted sum method to solve MOPs are the studies of Sandar (2019), Tram andRaweewan (2021), andThippo et. al.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-Objective Job Rotation in Rice Seed Harvesting With Equitable Injury Risk and Cost Allocation

Thippo,

Jaturanonda,

Yaovasuwanchai

et al. 2023

International Journal of Knowledge and Systems Science

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This article presents a non-linear multi-objective optimization model with four different objectives for manual rice seed harvesting, aiming to ensure members' fairness and mutual benefits for a group of rice field owners responsible for seed planting and a group of workers tasked with harvesting rice seeds. The harvesting plan primarily focuses on minimizing the average injury risk to workers and secondarily balances this risk among workers. Simultaneously, the model seeks to minimize and equitably allocate wage costs for rice field owners. Worker characteristics, including age, gender, and body mass index are considered to influence injury risk differentially. The optimal solution involves rotating workers to different rice stalk types in several fields, all within appropriate work and rest periods. This approach serves to prevent musculoskeletal disorders and fatigue among the workers while helping rice field owners reduce their costs. This collaborative planning has the potential to enhance sustainability within the farming community.

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A Scientometric Analysis of the Capacity Expansion and Planning Research

AlDurgam

Tuffaha

Abdel-Aal

et al. 2024

IEEE Trans. Eng. Manage.

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An optimization approach to capacity planning of aggregators and resource provisioning in cloud providers for meteorological sensor network

Cited by 3 publications

References 7 publications

Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review

Cloud-Based Internet of Things in Healthcare Applications: A Systematic Literature Review

Multi-Objective Job Rotation in Rice Seed Harvesting With Equitable Injury Risk and Cost Allocation

A Scientometric Analysis of the Capacity Expansion and Planning Research

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