| Autor: |
Iqbal Ahmad Dahlan, Suhono Harso Supangkat, Fadhil Hidayat, Fetty Fitriyanti Lubis |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
2021 International Conference on Artificial Intelligence and Mechatronics Systems (AIMS). |
| DOI: |
10.1109/aims52415.2021.9466044 |
| Popis: |
Nowadays, the railway industry has a public transport in a key position where it must be able to face the challenge of ensuring the safety and quality of service regarding health's safety in a pandemic situation. Public transport as a center of people's mobility must be safe to ensure visitors travel during the pandemic. This must be taken because the impact of COVID-19 has spread to almost all sectors and has also caused health facilities to experience the highest level of crisis. Many precautions need to be taken to reduce the spread of this disease where health care protocols must be adhered to with technology to control and manage smart railways resilience in the face of a pandemic. This paper proposes to implement CCTV analytics as a platform to process real-time data with a study case in Bandung Railway Station into knowledge displayed in a Viana Safe dashboard with accuracy 93.95% result on mask detection, social distancing to ensure the COVID-19 protocol with a real time speed of processing with NVIDIA 2080 Ti around of 25 FPS, 30 FPS of visitor counting and fever detection to screen the health status of visitor with accuracy 0.1-0.5'C of face temperature. It will send an early warning notification if the system detects the anomaly detection COVID-19 protocol violation. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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