I need a full-length, Q1-ready scientific article that explores how AI-enabled smart wearables boost productivity in healthcare settings. My angle is strictly case-study driven: I want real-world evidence drawn from hospitals, clinics, or telemedicine programs that have integrated sensors, smartwatches, or other wearable devices into their workflows. Please ground every section—introduction through conclusion—in rigorous data: peer-reviewed papers, publicly available datasets, or first-hand interviews if you can secure them. A clear link must be drawn between the AI components (analytics platforms, predictive algorithms, edge inference, etc.) and measurable productivity outcomes such as reduced nurse rounds, faster diagnostics, or lower readmission rates. Deliverables • 6,000–8,000-word manuscript formatted for a Scopus-indexed Q1 journal (choose a template like Elsevier’s if you don’t already have one). • Structured abstract (≤250 words), 4-6 keywords, graphical abstract optional but welcomed. • At least two detailed healthcare case studies with tables or figures summarising productivity metrics. • Complete reference list in APA 7th or IEEE (your choice, just be consistent) managed in EndNote, Zotero, or Mendeley. • Plagiarism report (<10 %) and a brief cover letter ready for journal submission. Acceptance criteria 1. Logical flow and depth suitable for peer reviewers at a high-impact journal. 2. All claims supported by citations or data; figures clearly labeled and original. 3. Turn-key submission package: manuscript file, high-resolution figures, separate highlights page, and cover letter. If you have prior publications on AI, wearables, or healthcare productivity, let me know in your bid and feel free to attach samples. I’m ready to start as soon as I select the right collaborator.