[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4884":3,"related-4884":66},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":9,"secondary_topics":21,"classification":22,"search_phrases":48,"slug":49,"view_count":15,"doi":50,"paper":51,"created_at":65},4884,"IoT-Enabled Predictive Analytics for Real-Time Decision-Making in Saudi Digital Service Platforms","https:\u002F\u002Fdoi.org\u002F10.64388\u002Firev10i4-1723953","Saudi digital service platforms are now becoming more reliant on connected devices, the streaming of telemetry data, and automated service orchestration, but the shift from simply observing events to being able to anticipate operational outcomes is still very uneven. This review looks at how Internet of Things (IoT)-based predictive analytics can assist with real-time decision-making in the various digital service environments in Saudi Arabia, focusing on the architectural, analytical and governance conditions needed for a reliable implementation. The study draws together evidence from peer-reviewed publications between 2020 and 2025 covering the topics of IoT, edge intelligence, machine learning, digital platforms, decision support, privacy, reliability and smart-city applications. Instead of viewing prediction as a separate algorithmic activity, the review presents it as a complete operational capability that involves sensing, data-quality control, contextual processing, model inference, decision policies, workflow execution and feedback on the outcomes. The evidence shows that the value obtained depends more on a low-latency architecture, trustworthy data, explainable decision thresholds, resilient connectivity and institutional ownership of the results than on the complexity of the models. For Saudi Arabia, these requirements are especially important since the country's digital transformation includes large-scale investments in infrastructure, high levels of mobile connectivity, smart-city projects and sector-specific service platforms. A reference architecture and a decision lifecycle are suggested in order to link IoT telemetry with predictive service operations while still ensuring security, privacy and human oversight. The review concludes that the most defensible approach is a federated, edge-cloud operating model in which predictive intelligence is incorporated into measurable service workflows and is governed by clear assurance controls.","沙特阿拉伯的数字服务平台如今越来越依赖互联设备、遥测数据流和自动化服务编排，但从单纯观察事件到能够预判运营结果的转变仍很不均衡。本综述探讨基于物联网（IoT）的预测分析如何协助沙特阿拉伯各类数字服务环境中的实时决策，重点关注可靠实施所需的架构、分析和治理条件。本研究汇集了2020年至2025年间经同行评审的出版物中的证据，涵盖物联网、边缘智能、机器学习、数字平台、决策支持、隐私、可靠性和智慧城市应用等主题。本综述不将预测视为一项单独的算法活动，而是将其呈现为一种完整的运营能力，涉及感知、数据质量控制、上下文处理、模型推理、决策策略、工作流执行以及结果反馈。证据表明，所获得的价值更多取决于低延迟架构、可信数据、可解释的决策阈值、有韧性的连接以及对结果的制度化归属，而非模型的复杂性。对沙特阿拉伯而言，这些要求尤为重要，因为该国的数字化转型包括基础设施的大规模投资、高水平的移动连接、智慧城市项目以及针对特定行业的服务平台。本文提出了一个参考架构和决策生命周期，以将物联网遥测与预测性服务运营联系起来，同时确保安全性、隐私和人工监督。本综述的结论是，最站得住脚的方法是一种联邦式边缘-云运营模式，其中预测智能被纳入可衡量的服务工作流，并受到明确保障控制措施的治理。",null,"Iconic Research and Engineering Journals","2026-10-12T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"内容为沙特数字服务平台IoT预测分析综述，与三农、农业信息化、智慧农业、数字乡村无关，不予入选。",[19],{"name":10,"url":6},[12],[],{"status":23,"locked":14,"version":24,"method":25,"evidence":26},"needs_review","2026-10-22.2","rules",{"candidates":27,"agricultural_evidence":14,"reason":47},[28,38],{"code":29,"score":30,"supported":31,"title":32,"abstract":34,"tags":37},"I5",17,true,[33],"IoT",[35,36,33],"物联网","internet of things",[],{"code":39,"score":40,"supported":31,"title":41,"abstract":42,"tags":46},"I2",9,[],[43,44,45],"机器学习","machine learning","decision support",[],"农业相关性需要复核",[],"IoT-EnabledPredictiveAnalyticsforReal-Ti-4884","10.64388\u002Firev10i4-1723953",{"doi":50,"openalex_id":52,"authors":53,"venue":10,"cited_by_count":15,"oa_url":57,"card":58,"direction":62,"ingested_from":64},"W7221519608",[54],{"name":55,"orcid":56},"Ahmed Helmi","https:\u002F\u002Forcid.org\u002F0000-0002-2233-9940","https:\u002F\u002Fwww.irejournals.com\u002Fformatedpaper\u002F1723953.pdf",{"tldr":59,"method":60,"finding":61,"direction":62,"opportunity":63},"综述沙特数字服务平台中基于物联网的预测分析如何支撑实时决策。","综述2020-2025年文献，涵盖物联网、边缘智能、机器学习与智慧城市应用。","预测价值更多取决于低延迟架构、可信数据与治理，而非模型复杂度。","智慧农业 \u002F 农业物联网","可将该边缘-云联邦预测架构迁移至农业物联网，研究农田实时决策与数据治理。","openalex","2026-10-14T23:30:10.425948Z",{"total":15,"page":67,"page_size":67,"items":68},1,[]]