Given the growth of different manufacturers with diverse hardware/software designs, growth of transducers functionalities, and rising concerns towards heterogeneity and data security and trustworthiness the Institute of Electrical and Electronics Engineers (IEEE) Instrumentation and Measurement Society’s - Technical Committee 9 - Sensor Technology (IM/ST - TC9 - Sensor Technology) supported by the National Institute of Standards and Technology (NIST) formalized the IEEE 1451 family of standards. The standards were developed with the purpose of defining common interfaces for communication within transducers and different systems with plug-and-play features, reducing configuration and deployment time. However, in the context of Industry 4.0 the standard lacks to address emerging technologies towards IoT applications, AI and remaining concerns related to cybersecurity, making it difficult to achieve a widespread adoption in the industry sector. This paper explores a systematic review using the Preferred Reporting Items for Systematic Reviews 2020 (PRISMA2020) as a formal systematic literature review guideline to collect and analyze existing knowledge within the scope of the IEEE 1451 standard, examine potential improvements to the standard, and explore future directions to address the constraints identified and open new research opportunities. A total of 53 studies are analyzed considering publications within the 2019 and 2025 time-frame, with data being collected from the Web of Science, Scopus, and IEEE Xplore scientific database. Findings reveal a strong focus on smart transducers applications in the most diverse domains with interoperability concerns, such as integration with different standards, smart cities applications, environmental monitoring, as well as researches on disseminating the adoption of the standards considering both the academic community and industry field, while also suggesting adaptations/modifications of particular parameters to address evolving applications. Furthermore, a portion of the findings are centered on cybersecurity vulnerabilities and propose solutions to enhance robustness and resilience of systems employing the given standards.

This paper presents initial developments towards a high-frequency condition monitoring framework designed for Autonomous Mobile Robots (AMRs) in Smart Factory environments. The proposed approach focuses on data acquisition and edge-level processing at the ultrasound range specifically (>20 kHz), using Micro-Electro-Mechanical System (MEMS) sensors. The system integrates real-time data acquisition, embedded fixed-point frequency-domain processing via a 1024-point FFT, and the integration of Industrial Internet-of-Things (IIoT) infrastructure based on the TIG (Telegraf, InfluxDB, and Grafana) stack, for data aggregation and remote visualization. To ensure timing precision at a sampling rate of 160 kHz, a software-based calibration routine is implemented to compensate for microcontroller overhead. Furthermore, the architecture’s alignment with IEEE 1451 principles is discussed to support interoperable and scalable sensor integration. Experimental results validate the reliable acquisition and processing of ultrasonic signals up to 80 kHz using controlled acoustic sources. This work provides a foundational infrastructure for condition-based monitoring, enabling future development of automated anomaly detection for mechanical components, such as bearings, which exhibit early-stage fault signatures in the ultrasonic spectrum.

This paper presents a digital twin demonstrator of a forest harvesters and wood processing machines. The demonstrator is a cyber-physical system that allow the emulation and identification of faults that may occur during regular machine operations. The proposed solution includes a CAN Bus communication between several electronic controller units connected to sensors and actuators.

Given the growth of different manufacturers with diverse hardware/software designs, growth of transducers functionalities, and rising concerns towards heterogeneity and data security and trustworthiness the Institute of Electrical and Electronics Engineers (IEEE) Instrumentation and Measurement Society's Technical Committee on Sensor Technology supported by the National Institute of Standards and Technology (NIST) formalized the IEEE 1451 family of standards. The standards were developed with the purpose of defining common interfaces for communication within transducers and different systems with plug-and-play features, reducing configuration and deployment time. However, in the context of Industry 4.0 the standard lacks to address emerging technologies towards IoT applications, AI and remaining concerns related to cybersecurity, making it difficult to achieve a widespread adoption in the industry sector. This paper explores a systematic review using the Preferred Reporting Items for Systematic Reviews 2020 (PRISMA2020) as a formal systematic literature review guideline to collect and analyze existing knowledge within the scope of the IEEE 1451 standard, examine potential improvements to the standard, and explore future directions to address the constraints identified and open new research opportunities. A total of 46 studies are analyzed in this paper considering publications within the 2019 and 2024 time-frame, with data being collected from the Web of Science, Scopus, and IEEE Xplore scientific database. Findings reveal a strong focus on smart transducers applications in the most diverse domains with interoperability concerns, such as integration with different standards, smart cities applications, environmental monitoring, as well as researches on disseminating the adoption of the standards considering both the academic community and industry field, while also suggesting adaptations/modifications of particular parameters to address evolving applications. Furthermore, a portion of the findings are centered on cybersecurity vulnerabilities and propose solutions to enhance robustness and resilience of systems employing the given standards.