Smart textiles have progressed from conventional passive sensing fabrics to advanced cyber-physical systems capable of integrating sensing, actuation, computation, and wireless communication within a single textile platform. With a focus on circular economy principles, this review critically examines intelligent textile ecosystems, from material architectures to AI-enabled wearable platforms. The functional hierarchy involves passive (sensing), active (sensing + response) and ultra-smart (autonomous decision making) textiles. The four classes of materials are metallic conductors, carbonaceous nanomaterials (CNTs and graphene), conductive polymers (PEDOT:PSS) and bio-based alternatives. Integration is achieved through coating, weaving, printing and additive manufacturing. Energy autonomy is achieved by five harvesting mechanisms: piezoelectric (1–10 µW·cm−2), triboelectric (10–100 µW·cm−2), thermoelectric (20–50 µW·cm−2), photovoltaic (100–1000 µW·cm−2) and bio-electrochemical (1–5 µW·cm−2). Hybrid systems can run continuously. Flexible supercapacitors and thin-film batteries are used for energy storage. The combination of AI and IoT allows for multi-tier architectures that encompass edge processing (TinyML), gateway management, and cloud analytics. On-device inference reduces energy consumption by 60–80%, improves privacy and enables real-time anomaly detection using CNNs, LSTMs and autoencoders. Sustainability is considered through life-cycle assessment, which quantifies impacts across extraction, fabrication, use, and end-of-life of materials. Circular strategies such as design for disassembly, harmonization of materials, biodegradable electronics, and recycling routes are all important. We critically evaluate key challenges such as manufacturing scalability, washability, biocompatibility, and regulatory standardization. This review provides a unifying framework that connects materials science, electronics, AI and sustainable design, providing a roadmap for circular, intelligent and energy-autonomous textile systems in line with UN SDGs (3, 9, 12, 13).
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Alam et al. (2026) studied this question.
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