• Practical architecture patterns for TinyML and in‑sensor edge processing that cut latency and radio use.
• Data pipeline recipes for intermittent connectivity: store‑and‑forward, prioritized queues, and idempotent reconciliation.
• Personalization strategies: on‑device calibration, few‑shot adaptation, and federated learning safeguards.
• Human factors and UX playbook: onboarding, alarm fatigue reduction, accessibility, and social acceptability.
• Security fundamentals: hardware root of trust, secure boot, signed OTA, key rotation, and attestation.
• Privacy by design checklist: DPIA, edge‑first analytics, pseudonymization, retention policies, and user dashboards.
• Regulatory pathway map: intended‑use classification, ISO 13485 QMS basics, ISO 14971 risk analysis, and clinical evidence planning.
• Power management tactics: power budgets, event‑driven sensing, sensor hubs, and realistic energy‑harvesting guidance.
• Connectivity decision matrix: BLE, Wi‑Fi, LPWAN tradeoffs, adaptive sync policies, and metered‑network UX.
• Testing and validation protocols: IQ/OQ/PQ, on‑body field trials, human‑factors studies, and postmarket surveillance.
• Safe model lifecycle: signed artifacts, A/B atomic swaps, delta updates, canary rollouts, and telemetry gating.
• Interoperability standards: compact schemas, schema registry, feature negotiation, and FHIR translation guidance.
• Manufacturing readiness: DFM, pilot runs, ICT/functional test plans, supplier qualification, and yield optimization.
• Business and monetization options: device+service, enterprise licensing, privacy‑first paid tiers, and unit‑economics checklist.
• Ethics and maintenance: bias audits, consent flows, incident playbooks, continuous monitoring, and end‑of‑life policies.

Bonus assets included: launch checklist, DPIA template, OTA rollout checklist, and a reproducible test protocol to accelerate your pilot.