WGW4IIoT: Wireless Gateway for Industrial IoT

Resende, Carlos; Monteiro, Manuel; Oliveira, João; Moreira, Waldir; Cavaleiro, Armando; Silva, Rui; Carvalho, Ricardo Tavares de

doi:10.1109/iscc.2018.8538656

Cited by 4 publications

(5 citation statements)

References 2 publications

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“…This allows it to be tailored to the Industry 4.0 architecture present at each deployment, and extended to support the feature set demanded by the application scenario. More details on ZeroMQ socket, Core API and Rest API are available in Section 3.2 and in [ 22 ].…”

Section: Our Proposed Tip40mentioning

confidence: 99%

“…These modules (highlighted with a solid/dashed black outline) are: the Intelligence Manager module, a new software module responsible for interfacing with the AI accelerator hardware; the database, adapted to include the new edge computing features; the database access APIs (Repository API, Core API, and Rest APIs) updated to provide access to the new feature of the system database; and the Web UI where the new features were exposed to the user. As the remaining elements were inherited from WGW4IIoT, we point the reader to [ 22 ] for further details.…”

Section: Our Proposed Tip40mentioning

confidence: 99%

“…Figure 5 , Figure 6 and Figure 7 presents some examples of the mentioned web interface screens. The web interfaces are named Tekon IoT Gateway as this is the commercial name used by Bresimar Automação S.A. for TIP4.0 and the solution presented in [ 22 ].…”

Section: Our Proposed Tip40mentioning

confidence: 99%

“…We introduce TIP4.0, a platform for PdM based on a modular software solution for edge computing gateways. TIP4.0 is built with an industry mindset on top of a previously proposed Wireless Gateway for Industrial IoT (WGW4IIoT) [ 22 ]. The platform is flexible enough to adapt to specific installation needs and provides support for further development when new requirements emerge in industry application scenarios.…”

Section: Introductionmentioning

confidence: 99%

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TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance

Resende

Folgado

Oliveira

et al. 2021

Sensors

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Industry 4.0, allied with the growth and democratization of Artificial Intelligence (AI) and the advent of IoT, is paving the way for the complete digitization and automation of industrial processes. Maintenance is one of these processes, where the introduction of a predictive approach, as opposed to the traditional techniques, is expected to considerably improve the industry maintenance strategies with gains such as reduced downtime, improved equipment effectiveness, lower maintenance costs, increased return on assets, risk mitigation, and, ultimately, profitable growth. With predictive maintenance, dedicated sensors monitor the critical points of assets. The sensor data then feed into machine learning algorithms that can infer the asset health status and inform operators and decision-makers. With this in mind, in this paper, we present TIP4.0, a platform for predictive maintenance based on a modular software solution for edge computing gateways. TIP4.0 is built around Yocto, which makes it readily available and compliant with Commercial Off-the-Shelf (COTS) or proprietary hardware. TIP4.0 was conceived with an industry mindset with communication interfaces that allow it to serve sensor networks in the shop floor and modular software architecture that allows it to be easily adjusted to new deployment scenarios. To showcase its potential, the TIP4.0 platform was validated over COTS hardware, and we considered a public data-set for the simulation of predictive maintenance scenarios. We used a Convolution Neural Network (CNN) architecture, which provided competitive performance over the state-of-the-art approaches, while being approximately four-times and two-times faster than the uncompressed model inference on the Central Processing Unit (CPU) and Graphical Processing Unit, respectively. These results highlight the capabilities of distributed large-scale edge computing over industrial scenarios.

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Section: Our Proposed Tip40mentioning

confidence: 99%

Section: Our Proposed Tip40mentioning

confidence: 99%

Section: Our Proposed Tip40mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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TIP4.0: Industrial Internet of Things Platform for Predictive Maintenance

Resende

Folgado

Oliveira

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

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“…Pengembangan Internet of Things (IoT) pada berbagai bidang juga menyebabkan terjadinya perubahan sistem pada sektor industri yang ditandai dengan digitalisasi sistem produksi dan proses industri yang kemudian dikenal dengan visi Industri 4.0 atau revolusi industri keempat. Digitalisasi proses produksi ketika diterapkan dapat memiliki dampak positif untuk menghasilkan produk yang berkualitas (Resende et al, 2018).…”

Section: Pendahuluanunclassified

Optimalisasi Sistem Monitoring Temperatur Logam Cair pada Proses Pengecoran menggunakan Pyrometer Berbasis Internet of Things (IoT)

Fathurrohman

Eryantono

Rumbara

2021

TEKNIK

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Perkembangan teknologi berbasis internet yang pesat menyebabkan terjadinya perubahan pada sektor industri yang dikenal dengan Revolusi Industri 4.0. Industri manufaktur pengecoran merupakan salah satu sektor industri yang harus beradaptasi dengan perkembangan industri 4.0 agar dapat bersaing dalam meningkatkan kualitas produk coran. Beberapa parameter yang mempengaruhi kualitas produk coran adalah temperatur saat penuangan (pouring) dan laju penuangan. Penentuan temperatur penuangan harus memperhitungkan faktor kehilangan panas yang disebabkan oleh waktu pemindahan logam cair dan kondisi lingkungan sekitar. Penentuan temperatur tuang yang kurang tepat dapat menyebabkan terbentuknya porositas (rongga) pada produk hasil pengecoran. Karena pentingnya penentuan temperatur tersebut, maka pada penelitian ini dibangun sistem monitoring berbasis internet of things (IoT) untuk memantau temperatur logam cair saat proses pengecoran secara real-time. Sistem yang dibangun terdiri atas tiga bagian, yaitu: sensor temperatur, gateway dan server. Perangkat pyrometer digunakan untuk mengukur temperatur logam cair dan mengirimkannya ke gateway. Perangkat gateway kemudian mengirimkan data tersebut ke server. Pengguna dapat mengamati temperatur logam cair secara real-time melalui website. Hasil penelitian menunjukkan bahwa dengan sistem monitoring berbasis IoT ini, dapat diperoleh database pengukuran temperatur logam cair yang optimal. Tingkat keakuratan pengukuran data temperatur tersebut mencapai 99,5%.

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