Proactive Fault Detection in Weather Forecast Control Systems Through Heartbeat Monitoring and Cloud‐Based Analytics

Опубликована: Фев. 7, 2025

Язык: Английский

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An effective crop recommendation method using machine learning techniques

International Journal of Advanced Technology and Engineering Exploration, Год журнала: 2023, Номер 10(102)

Опубликована: Май 31, 2023

In recent years, there have been drastic climatic changes occurring because of global warming [58].The selection inappropriate crops has a tremendous impact on farmer's hopes and dreams it uses up all available resources (such as the cost seeds, fertilizers, etc.Using machine learning (ML) key technology, traditional farming can be reshaped.This research aims to introduce ML-based crop suggestion system for farmers, hoping use this information produce more productive higher-quality with less waste.ML recommends suitable using various mathematical or statistical methods.By employing these methods, we advise farmer most grow in his particular agricultural region, helping him maximize profits.To help farmers make informed decisions about what grow, are classified according nutrients they contain.Classification is ML technique that enormous potential sector.Different classifiers currently purpose [9].Classification training data categorize new

Язык: Английский

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TCP Performance Enhancement in IoT and MANET: A Systematic Literature Review

International Journal of Computer Networks And Applications, Год журнала: 2023, Номер 10(4), С. 543 - 543

Опубликована: Авг. 31, 2023

TCP operates as a unicast protocol that prioritizes the reliability of established connections.This allows for explicit and acknowledged establishment dissolution connections, transmission data without loss context or duplication, management traffic flows, avoidance congestion, asynchronous signaling time-sensitive information.In this research, we use Systematic Literature Review (SLR) technique to examine better understand several methods recently given enhancing performance in IoT MANET networks.This work aims assess classify current research strategies on approaches published between 2016 2023 using both analytical statistical methods.Technical parameters suggested case study evaluation settings are compared give taxonomy improvement options based content studies chosen SLR procedure.Each study's merits limitations outlined, along with suggestions improving those areas where further is needed.This outlines basic issues when it used MANET.It also highlights recent enhancement, such machine Learning-based approaches, multi-path TCP, congestion control, buffer management, route optimization.It provides potential future directions into effectiveness MANET.The major findings review provide thorough understanding latest techniques networks, which can be beneficial researchers practitioners field networking.

Язык: Английский

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Spatial analysis and technological influences on smart city development in Kazakhstan

Journal of Infrastructure Policy and Development, Год журнала: 2023, Номер 8(2)

Опубликована: Дек. 20, 2023

This study delves into the evolving landscape of smart city development in Kazakhstan, a domain gaining increasing relevance context urban modernization and digital transformation. The research is anchored quest to understand how specific technological factors influence formation cities within region. To this end, adopts Spatial Autoregressive Model (SAR) as its core analytical tool, leveraging data on server density, cloud service usage, electronic invoicing practices across various Kazakhstani cities. crux revolves around assessing impact these selected variables process. SAR model’s application facilitates nuanced understanding spatial dynamics at play, offering insights vary different areas. A key finding investigation significant positive correlation between adoption development, result that stands contrast relatively insignificant density usage. conclusion drawn from findings underscores pivotal role administrative processes, particularly invoicing, driving agenda Kazakhstan. insight not only contributes academic discourse but also holds practical implications for policymakers planners. It suggests strategic shift towards prioritizing innovations over mere infrastructural or upgrades. study’s outcomes are poised guide future initiatives Kazakhstan offer reference point similar emerging economies embarking their journeys.

Язык: Английский

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5G and IoT Cloud Integration for Enhancing Connectivity and Data Management

Опубликована: Март 11, 2024

This research analyzed the result of super-fast 5G networks on IoT and explores how cloud can enhance performance execution smart devices in conjunction with 5G. The arrival 5G, akin to a next-level internet, enables rapid low-latency communication between sensors devices. Leveraging cloud, which serves as vast computing resource further optimize capabilities these environment. incorporation 5 ^th Generation offers several significant outcomes. Firstly, it enhances connectivity by facilitating seamless real-time data exchange among devices, enabling efficient interactions improving overall system performance. Secondly, provides additional capacity storage capacity, offload processing tasks handle large volumes generated effectively. capability operational efficiency, particularly domains such self-driving cars manufacturing, where decision-making advanced automation are critical. Moreover, cloud's scalability flexibility empower adapt dynamically changing demands. allows businesses individuals scale their resources needed, eliminating need for substantial infrastructure investments. Additionally, addresses concerns regarding management security. By exploring cloud-based handling techniques, ensures while safeguarding privacy implementing robust security measures interconnected ecosystem. In conclusion, this aims establish symbiotic relationship networks, cloud. Through integration, envisions more connected ecosystem, driving advancements various industries, enhancing automation, delivering an optimized user experience upholding

Язык: Английский

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Implementation of Cloud Computing and Internet of Things (IoT) by Performance Evaluation

Опубликована: Март 6, 2024

The integration of cloud computing and the Internet Things (IoT) holds transformative potential across diverse industries. Performance assessment is essential to gauge quality efficiency IoT systems. This paper presents a comprehensive performance evaluation systems, focusing on three major platforms: Amazon Web Services (AWS), Google Cloud Platform (GCP), Microsoft Azure. Experimental results encompass various scenarios, including normal operation, heavy load conditions, applications, scalability testing. outcomes reveal distinct metrics such as response time, throughput, latency, reliability for each platform.

Язык: Английский

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IoT Cloud Ecosystems

Advances in educational technologies and instructional design book series, Год журнала: 2024, Номер unknown, С. 247 - 280

Опубликована: Дек. 20, 2024

The internet of things (IoT) cloud refers to an internet-based platform that facilitates the storage, management, and analysis data generated by IoT devices. It combines capabilities computing with connectivity IoT, creating a powerful ecosystem supports wide range applications services providers are essential because they provide infrastructure required for efficient deployment management solutions. In order address multiple service areas, including application development, device administration, system heterogeneity tools applicability, this chapter analyses well-known platforms. A few issues researchers should in near future also described. This chapter's ultimate objective is impart thorough knowledge about current providers.

Язык: Английский

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