Applications of Carbon-Based Multivariable Chemical Sensors for Analyte Recognition

• Carbon-based multivariable chemical sensors using CNTs/graphene and FET transducers enable analyte recognition with a single sensing material, overcoming limitations of monovariable sensors and complex sensor arrays. • The review provides a comprehensive analysis of multivariable sensing mechanisms and design criteria, highlighting the role of pattern recognition algorithms in enhancing selectivity and classification. • Innovative multivariable extraction schemes integrated with advanced algorithms demonstrate practical applications in environmental monitoring, industrial production, and medical diagnostics. • The work underscores the potential of carbon-based sensors for low-cost, compact, and portable real-time monitoring in IoT and industrial internet contexts.