{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T11:25:47Z","timestamp":1780658747415,"version":"3.54.1"},"reference-count":34,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2022,4,15]],"date-time":"2022-04-15T00:00:00Z","timestamp":1649980800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Ultra-low-power is a key performance indicator in 6G-IoT ecosystems. Sensor nodes in this eco-system are also capable of running light-weight artificial intelligence (AI) models. In this work, we have achieved high performance in a gas sensor system using Convolutional Neural Network (CNN) with a smaller number of gas sensor elements. We have identified redundant gas sensor elements in a gas sensor array and removed them to reduce the power consumption without significant deviation in the node\u2019s performance. The inevitable variation in the performance due to removing redundant sensor elements has been compensated using specialized data pre-processing (zero-padded virtual sensors and spatial augmentation) and CNN. The experiment is demonstrated to classify and quantify the four hazardous gases, viz., acetone, carbon tetrachloride, ethyl methyl ketone, and xylene. The performance of the unoptimized gas sensor array has been taken as a \u201cbaseline\u201d to compare the performance of the optimized gas sensor array. Our proposed approach reduces the power consumption from 10 Watts to 5 Watts; classification performance sustained to 100 percent while quantification performance compensated up to a mean squared error (MSE) of 1.12 \u00d7 10\u22122. Thus, our power-efficient optimization paves the way to \u201ccomputation on edge\u201d, even in the resource-constrained 6G-IoT paradigm.<\/jats:p>","DOI":"10.3390\/s22083039","type":"journal-article","created":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T02:39:31Z","timestamp":1650335971000},"page":"3039","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Zero-Padding and Spatial Augmentation-Based Gas Sensor Node Optimization Approach in Resource-Constrained 6G-IoT Paradigm"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5436-2977","authenticated-orcid":false,"given":"Shiv Nath","family":"Chaudhri","sequence":"first","affiliation":[{"name":"Department of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1650-011X","authenticated-orcid":false,"given":"Navin Singh","family":"Rajput","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2857-6979","authenticated-orcid":false,"given":"Saeed Hamood","family":"Alsamhi","sequence":"additional","affiliation":[{"name":"Software Research Institute, Technological University of the Shannon, Midlands Midwest, N37HD68 Athlone, Ireland"},{"name":"Faculty of Engineering, IBB University, Ibb 70270, Yemen"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexey V.","family":"Shvetsov","sequence":"additional","affiliation":[{"name":"Department of Operation of Road Transport and Car Service, North-Eastern Federal University, 677000 Yakutsk, Russia"},{"name":"Department of Transport and Technological Processes, Vladivostok State University of Economics and Service, 690014 Vladivostok, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1291-055X","authenticated-orcid":false,"given":"Faris A.","family":"Almalki","sequence":"additional","affiliation":[{"name":"Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif 21944, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Galkin, P., Golovkina, L., and Klyuchnyk, I. 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