Machine Vision Systems for Smart Cities: Applications and Challenges

Tiwari, Shamik; Jain, Anurag

doi:10.1007/978-981-19-2940-3_18

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…As manufacturing processes become more automated and the need for rapid component identification escalates, AIvision systems play an increasingly pivotal role [23]. Their ability to swiftly and accurately classify components enhances production rates, reduces the chances of assembly errors, and ensures consistent product quality.…”

Section: Applications Of Ai-vision In Component Identification In Man...mentioning

confidence: 99%

Efficient decision-making in SMEs: leveraging knowledge graphs with Neo4j and AI vision

Mo,

Rehman,

Elshafei

et al. 2023

Low-Cost Digital Solutions for Industrial Automation (LoDiSA 2023)

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In the evolving digital landscape, Small and Medium-sized Enterprises (SMEs) grapple with the intricate task of managing vast manufacturing data while operating within budgetary constraints. Addressing this dichotomy, our research introduces an innovative and cost-conscious solution that marries the capabilities of Neo4j's knowledge graph with an AI-enhanced vision system. This integrated system adeptly captures realtime manufacturing data, including product images, configuration details, and specific parameters relevant to the leak testing process. This data is subsequently structured within a comprehensive knowledge graph, enabling SMEs to derive actionable insights and optimize their manufacturing decisions. By harnessing the affordability and scalability of Neo4j's cloud service, the approach we propose stands as a beacon for SMEs, positioning them for enhanced precision in leak testing, operational efficiency, and sustained growth in the digitized economy.

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Section: Applications Of Ai-vision In Component Identification In Man...mentioning

confidence: 99%