Overcrowding during indoor events can be risky, in-case of any kind of a hazard such as fire.This solution address this by providing real-time crowd detection solution using Force-SensingResistor (FSR) sensors, referred sensor (IR) and microcontrollers. The solution needs to offer accurate data in real-time to the event managers including number of people and entrancerate to help when and if the event areas will be overcrowded, thereby enhancing event safetyand decision-making. This thesis indicate that the system offers essential real-time data forevent safety with an accuracy of 87.25%. These data will assists event managers in makinginformed decisions to avoid the risks of overcrowding. This thesis evaluates the effectivenessof our system in comparison to other systems, discussing what we’ve learned, suggest possibleimprovements, and talk about whether our system could be useful in real-world indoor events.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-127612 |
| Date | January 2024 |
| Creators | Hama, Mohamad |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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