ea9b533a0386a9bac9d2b0554515841c sensors-25-02590.pdf 87a5f81e50c56822e8f036ad34fdc26e32a0d039 sensors-25-02590.pdf e94e20c84d428084a8ccdfd273267f85c40f9055ef15f1b3a20317bda4256a37 sensors-25-02590.pdf Title: Enhanced Heat-Powered Batteryless IIoT Architecture with NB-IoT for Predictive Maintenance in the Oil and Gas Industry Subject: The carbon footprint associated with human activity, particularly from energy-intensive industries such as iron and steel, aluminium, cement, oil and gas, and petrochemicals, contributes significantly to global warming. These industries face unique challenges in achieving Industry 4.0 goals due to the widespread adoption of industrial Internet of Things (IIoT) technologies, which require reliable and efficient power solutions. Conventional wireless devices powered by lithium batteries have limitations, including a reduced lifespan in high-temperature environments, incompatibility with explosive atmospheres, and high maintenance costs. This paper proposes a novel approach to address these challenges by leveraging residual heat to power IIoT devices, eliminating the need for batteries and enabling autonomous operation. Based on the Seebeck effect, thermoelectric energy harvesters transduce waste heat from industrial surfaces, such as pipes or chimneys, into sufficient electrical energy to power IoT nodes for applications like the condition monitoring and predictive maintenance of rotating machinery. The methodology presented standardises the modelling and simulation of Waste Heat Recovery Systems (IoT-WHRSs), demonstrating their feasibility through statistical analysis of IoT-WHRS architectures. Furthermore, this technology has been successfully implemented in a petroleum refinery, where it benefits from the NB-IoT standard for long-range, robust, and secure communications, ensuring reliable data transmission in harsh industrial environments. The results highlight the potential of this solution to reduce costs, improve safety, and enhance efficiency in demanding industrial applications, making it a valuable tool for the energy transition. Keywords: energy harvesting; thermoelectricity; LCA; carbon footprint; NB-IoT; edge computing; NETZERO; energy-intensive industry Author: Raúl Aragonés, Joan Oliver and Carles Ferrer Creator: LaTeX with hyperref Producer: pdfTeX-1.40.25 CreationDate: Sat Apr 19 11:24:08 2025 CEST ModDate: Sat Apr 19 11:28:06 2025 CEST Custom Metadata: no Metadata Stream: no Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 25 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 11409377 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- MIKRSI+VnURWPalladioL Type 1 Custom yes yes yes 10 0 ZQDTVR+URWPalladioL-Roma Type 1 Custom yes yes yes 16 0 PUCXMP+URWPalladioL-Bold Type 1 Custom yes yes yes 22 0 OIXACZ+URWPalladioL-Ital Type 1 Custom yes yes yes 27 0 WMBHLE+SFTT1000 Type 1 Custom yes yes yes 53 0 EFENOG+PalatinoLinotype,Bold TrueType 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PDFMetadata: Objects: 1967 FreeObjects: 1 IncrementalUpdates: 0 DocumentCatalog: PageLayout: SinglePage PageMode: UseNone Outlines: Item: Title: Introduction Destination: section.1 Item: Title: Industrial IoT Application for Predictive Maintenance Destination: section.2 Children: Item: Title: Main Benefits Destination: subsection.2.1 Item: Title: Velocity Measurement Destination: subsection.2.2 Item: Title: Spectral Analysis for Fault Diagnosis Destination: subsection.2.3 Item: Title: Heat-Powered IIoT Architecture Destination: section.3 Children: Item: Title: Introduction to IoT-WHRS Architecture Destination: subsection.3.1 Item: Title: IoT-WHRS Model Parametrisation Destination: subsection.3.2 Item: Title: Thermal Modelling of IoT-WHRS Destination: subsection.3.3 Children: Item: Title: Heat Transfer Contribution via the TEG Channel Destination: subsubsection.3.3.1 Item: Title: Heat Transfer Modeling via the TEG Channel Destination: subsubsection.3.3.2 Item: Title: TEG Effective Parameters Model Destination: subsection.3.4 Item: Title: IoT-WHRS Finite Difference Model Destination: subsection.3.5 Item: Title: Edge Computing for Batteryless Device with NB-IoT Destination: section.4 Children: Item: Title: Eliminating Batteries: A New Paradigm for IIoT Monitoring Destination: subsection.4.1 Item: Title: Overcoming Technological Barriers for Wireless IIoT Destination: subsection.4.2 Item: Title: NB-IoT: The Optimal Protocol for Industrial Applications Destination: subsection.4.3 Item: Title: Internal Architecture of the Edge-Computing Node Destination: subsection.4.4 Item: Title: Data Acquisition, Processing, and Communication Flow Destination: subsection.4.5 Item: Title: Results Destination: section.5 Children: Item: Title: WHRU Characterisation Destination: subsection.5.1 Children: Item: Title: Simulation Results Destination: subsubsection.5.1.1 Item: Title: Experimental Results Destination: subsubsection.5.1.2 Item: Title: Statistical Results Destination: subsubsection.5.1.3 Item: Title: IIoT Node Power Characterisation Destination: subsection.5.2 Item: Title: Pilot Installation in a Hot Water Pump Destination: subsection.5.3 Item: Title: NB-IoT Connectivity Performance in a Harsh Industrial Environment Destination: subsection.5.4 Item: Title: Scalability of the IoT-WHRS Solution to Other Temperature Regimes Destination: subsection.5.5 Item: Title: Deployment Context and Industrial Considerations Destination: section.6 Children: Item: Title: Background and Related Work Destination: subsection.6.1 Item: Title: Cost and Operational Reliability Considerations Destination: subsection.6.2 Item: Title: Conclusions Destination: section.7 Item: Title: References Destination: section.8 Info: Title: Enhanced Heat-Powered Batteryless IIoT Architecture with NB-IoT for Predictive Maintenance in the Oil and Gas Industry Author: Raúl Aragonés, Joan Oliver and Carles Ferrer Subject: The carbon footprint associated with human activity, particularly from energy-intensive industries such as iron and steel, aluminium, cement, oil and gas, and petrochemicals, contributes significantly to global warming. These industries face unique challenges in achieving Industry 4.0 goals due to the widespread adoption of industrial Internet of Things (IIoT) technologies, which require reliable and efficient power solutions. Conventional wireless devices powered by lithium batteries have limitations, including a reduced lifespan in high-temperature environments, incompatibility with explosive atmospheres, and high maintenance costs. This paper proposes a novel approach to address these challenges by leveraging residual heat to power IIoT devices, eliminating the need for batteries and enabling autonomous operation. Based on the Seebeck effect, thermoelectric energy harvesters transduce waste heat from industrial surfaces, such as pipes or chimneys, into sufficient electrical energy to power IoT nodes for applications like the condition monitoring and predictive maintenance of rotating machinery. The methodology presented standardises the modelling and simulation of Waste Heat Recovery Systems (IoT-WHRSs), demonstrating their feasibility through statistical analysis of IoT-WHRS architectures. Furthermore, this technology has been successfully implemented in a petroleum refinery, where it benefits from the NB-IoT standard for long-range, robust, and secure communications, ensuring reliable data transmission in harsh industrial environments. The results highlight the potential of this solution to reduce costs, improve safety, and enhance efficiency in demanding industrial applications, making it a valuable tool for the energy transition. 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320 Annotation: Subtype: Link Rect: 56, 296, 103, 307 Annotation: Subtype: Link Rect: 204, 284, 560, 295 Annotation: Subtype: Link Rect: 56, 271, 247, 282 Checksum: c511b45c Type: CRC32 Checksum: ea9b533a0386a9bac9d2b0554515841c Type: MD5 Checksum: 87a5f81e50c56822e8f036ad34fdc26e32a0d039 Type: SHA-1 Checksum: e94e20c84d428084a8ccdfd273267f85c40f9055ef15f1b3a20317bda4256a37 Type: SHA-256