The Internet of Things (IoT) increasingly combines sensing, communication, artificial intelligence (AI), decision-making, and actuation. In many domains, sensor observations are processed by edge or cloud intelligence to select actions that configure or control actuators; where actuation changes the environment, later observations may also be affected. Existing explainable AI (XAI) methods can explain model predictions, but they do not by themselves explain the end-to-end path from sensed evidence to physical action. This paper introduces the Internet of Explainable Things (IoXT), a system-level paradigm that makes explainability an architectural property of intelligent IoT. Its novelty is explainability-by-design across the sensing-communication-intelligence-decision-actuation path. IoXT derives requirements and design principles for identity and addressability, temporal fidelity, cross-layer provenance, bidirectional traceability, streaming and incident-time evidence, protocol-semantic continuity, security and privacy, lifecycle continuity, and conformance. We formalize timestamped provenance graphs, sensor participation, trace completeness, cross-layer coverage, reconstruction latency, and No Orphan Actuation: a consequential action must remain traceable to the authorizing decision and source evidence, or be explicitly marked degraded or non-conformant. IoXT prescribes neither a particular XAI method nor a wire protocol. Instead, it defines the conditions under which model explanations remain connected to real sensor inputs, communication history, decisions, actuator execution, and outcomes. Explainability Telemetry Protocols (XTPs) are introduced as a protocol category for preserving these semantics across heterogeneous IoT systems, together with IoXT-ready and IoXT-conformant assurance concepts.

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