The technical standards are employed in everyday tasks, such as connecting to the internet or to nearby devices. The process to learn a new technical standard is difficult and needs time, as the standards have complex documentation that needs to be understood and comprehended. Based on that, a new proposed Web-based educational tool for e-learning has been developed to allow students and professors to speed up the learning curve for the IEEE 1451 family of standards using an interactive method, where the users fill in the fields with some inputs, and the tool shows its results in real time. This tool enables users to learn the IEEE 1451 Transducer Electronic Data Sheets (TEDS), the network service and transducer service messages from the IEEE 1451 Application (APP) to the IEEE 1451 Network Capable Application Processor (NCAP) and the NCAP to the Transducer Interface Module (TIM), respectively. The tool has been tested in the last two years by IEEE 1451 community members, professors, and students. Initial feedback suggests that this Web-based tool enhances the learning process and a deeper understanding of the IEEE 1451 family of standards, offering a promising approach to technical standards education.

Digital twins (DTs) are virtual replicas of physical assets, systems, and processes that enable real-time monitoring, simulation, and analysis to improve decision-making, optimize operations, increase efficiency, and achieve cost savings across various Internet of Things (IoT) applications. This paper introduces an IEEE 1451-based smart transducer digital twin framework (DTF) for IoT real-time monitoring and control applications. The framework consists of an IEEE 1451-based smart transducer physical twin (PT), its corresponding digital twin (DT), and a bidirectional information exchange between them for real-time monitoring and control. In this paper, the IEEE 1451.0 and P1451.1.6-based smart transducer DT is developed using the Node-RED platform and message queue telemetry transport (MQTT) protocol. The PT is developed using embedded devices, and a sensor and actuator development kit. The PT and DT communicate using 1451.0 and P1451.1.6 messages to exchange temperature sensor data for controlling the temperature of a smart home in real-time. The monitoring and control results of the smart home are provided in the paper to test and validate that the physical twin and digital twin work correctly.

The Internet of Things (IoT) is highly heterogeneous regarding smart sensors/devices, connectivity, communication protocols, and data formats. The major challenges of IoT ecosystems are fragmentation (or disintegration) and cross-domain interoperability. To overcome the challenges of interoperability, standardized interfaces and protocols, harmonized interactions, and interoperability testing are essential. This paper introduces a harmonization model of interactions among IoT devices with diverse interfaces/connectivity and communication protocols to achieve interoperability by harmonizing their interactions. A harmonization implementation of interactions of the IEEE 1451-based IoT devices and MODBUS devices has been provided in the paper to test and verify that the proposed harmonization model works well. This harmonization model and implementation of interactions among IoT devices will provide a solid foundation for the IEEE P1451.99 standard specification.

Modern edge artificial intelligence (AI) chipsets and edge-intelligence-enabled smart sensors frameworks support real-time data processing and event detection at the signal source. Beyond measuring local conditions and transmitting corresponding signals, AI-enabled smart sensors provide the capability to interpret and analyze signals through local analytical operations. Its well-known semantics provide an abstraction layer for better comprehension and self-descriptive applications. This paper identifies and explains the advantages of semantics and ontology engineering in integrating edge AI-enabled smart sensors and their applications into federated automotive systems. Building on demonstrated work using AudioSet for event detection, the application presented as an AI mechanic at the edge demonstrates how smart sensor integration necessitates the re-evaluation of how automotive diagnostic trouble codes (DTCs) are generated and processed. While DTCs and their logic are intended to facilitate correct assembly and repair, they do not always clearly indicate the underlying issue. This paper also underlines the need to review ontologies and semantic models for smart sensor standard specifications in light of AI-enabled smart sensors.

There are many challenges for Internet of Things (IoT) sensor networks including the lack of robust standards, diverse wireline and wireless connectivity, interoperability, security, and privacy. Addressing these challenges, the Institute of Electrical and Electronics Engineers (IEEE) P1451.0 standard defines network services, transducer services, transducer electronic data sheets (TEDS) format, and a security framework to achieve sensor data security and interoperability for IoT applications. This paper proposes a security solution for IEEE P1451.1.6-based sensor networks for IoT applications utilizing the security framework defined in IEEE P1451.0. The proposed solution includes an architecture, a security policy with six security levels, security standards, and security TEDS. Further, this paper introduces a new service to update access control lists (ACLs) to regulate the access for topic names by the applications and provides an implementation of the security TEDS for IEEE P1451.1.6-based sensor networks. The paper also illustrates how to access security TEDS that contain metadata on security standards to achieve sensor data security and interoperability.

Internet of Things (IoT) ecosystems are highly heterogeneous regarding smart sensors/devices, connectivity, communication protocols, data formats, and platforms. The major challenges of IoT ecosystems are fragmentation or disintegration and cross-domain interoperability. The Web of Things (WoT) integrates the IoT with Web technologies to address these IoT challenges. Semantic WoT (SWoT) integrates the WoT with Semantic Web technologies to achieve semantic interoperability of IoT ecosystems. Aiming to promote semantic communication, thus achieving semantic interoperability of the IEEE 1451.0based sensor networks for IoT applications, this paper introduces the IEEE 1451.0-based WoT ontology. An IEEE 1451.0-based WoT thing model is developed based on the combination of the IoT thing capability model and the World Wide Web Consortium (W3C) WoT thing model. The IEEE 1451.0-based WoT thing model consists of identification and context, behaviors, properties and data schema, security, time synchronization and protocol bindings for IEEE 1451 WoT Things – e.g., network-capable application processors (NCAP), application (APP), transducer interface modules (TIM), and smart transducers (sensors and/or actuators). A WoT thing description (TD) example of an IEEE 1451.0-based smart sensor is provided in the paper to verify the developed IEEE 1451.0-based WoT ontology.

It is vital to establish a suitable thermal environment for greenhouses to improve production quality for crop cultivation. However, in greenhouse environments, uneven temperature, caused by the influence of outside temperature, leads to unevenness in air conditioning and results in sub-optimized crop quality and yield. This paper introduces a real-time temperature monitoring and airflow controlling system using IEEE P1451.0 and P1451.1.6 standards to balance and improve greenhouse environments. The controlling system consists of three components: an infrared array of smart temperature sensors (STS) placed inside and outside the greenhouse, a smart airflow controller (SAC), and a temperature monitoring and airflow control application (TMACA). The network communications among STS, TMACA, and SAC are based on IEEE P1451.0 and P1451.1.6 standard network services using the message queuing telemetry transport (MQTT) protocol. In the system, the TMACA can monitor the temperatures inside and outside the greenhouse using two STS, process and estimate the temperature differences inside the greenhouse, and then control and equalize the temperature of the greenhouse using the SAC based on the temperature differences to balance and improve the greenhouse environment.

This paper introduces the time synchronization approaches to the Institute of Electrical and Electronics Engineers (IEEE) P1451.0 standard-based sensor networks for Internet of Things (IoT) applications. A time synchronization architecture of IEEE P1451.0 standard-based sensor networks is described including two-level time synchronization systems in IEEE P1451.0 and P1451.1.X standards-based wide-area network (WAN) and IEEE P1451.0 and P1451.5.X standards-based local area networks (LANs). However, this paper mainly focuses on the time synchronization approach of IEEE P1451.0 and P1451.1.6 standards-based WANs and provides two implementations of time synchronization of IEEE P1451.0 and P1451.1.6 using wireline and wireless networks with their preliminary results to verify that the time synchronization approach of IEEE P1451.1.6 functions properly. In addition, the time synchronization transducer electronic data sheets (TEDS) of P1451.1.6 is described.

The challenges of the Internet of Things (IoT) sensor networks include connectivity, interoperability, security, and privacy. The Institute of Electrical and Electronics Engineers (IEEE) P1451.0 standard is being revised based on these challenges and requirements to achieve sensor data interoperability and security for IoT applications. This paper analyzes the security requirements of sensor networks for IoT applications and proposed security solutions for IEEE P1451.0-based IoT sensor networks. It specifies security policies and levels of IEEE P1451.0-based sensor networks to meet the security requirements and defines security transducer electronic data sheets (TEDS) to describe security protocol information for IEEE P1451.0-based sensor networks. An implementation of the security TEDS for IEEE P1451.0 and P1451.5-802.11 wireless sensor networks is provided to illustrate how to access security TEDS that contain detailed security parameters and information to achieve sensor data security and interoperability.

Intelligent agents can enable the integration of preliminary design with manufacturing planning software systems. These agents execute in a computer-based collaborative environment called a "multi-agent platform." A prototype agent platform supporting the integration of preliminary design and manufacturing planning has been developed at NIST. These agents have access to a knowledge base that is implemented by rules, generated by mapping design information to process and resource selections. The rules are derived from an analysis of design factors that influence process and resource planning, such as product material, form, shape complexity, features, dimension, tolerance, surface condition, and production volume. Process planning agents provide process planners with information regarding selection of preliminary manufacturing processes, determining manufacturing resources, and constructing feedback information to product designers. The agent platform enables information exchange among agents based on the integrated object model. The main purposes of developing such a platform are to support product preliminary design, optimize product form and structure, and reduce manufacturing cost in the early design process.