The 4th Industrial Revolution and Its Impact on Entrepreneurial Education

Culduz, Murat

doi:10.4018/979-8-3693-0409-9.ch009

Cited by 1 publication

(1 citation statement)

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“…In recent days, the forthcoming Fourth Industrial Revolution, particularly the widespread use of artificial intelligence (AI)-whether in its narrow form (as a means to streamline simple, repetitive processes) or its general form-is poised to alter our daily lives significantly [1,2]. As such, our goal should be to create new systems that will enable society to flourish, guiding this digital transition through sophisticated computer architectures and infrastructures to influence our everyday decisions.…”

Section: Introductionmentioning

confidence: 99%

Streamline Intelligent Crowd Monitoring with IoT Cloud Computing Middleware

Gazis,

Katsiri

2024

Sensors

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This article introduces a novel middleware that utilizes cost-effective, low-power computing devices like Raspberry Pi to analyze data from wireless sensor networks (WSNs). It is designed for indoor settings like historical buildings and museums, tracking visitors and identifying points of interest. It serves as an evacuation aid by monitoring occupancy and gauging the popularity of specific areas, subjects, or art exhibitions. The middleware employs a basic form of the MapReduce algorithm to gather WSN data and distribute it across available computer nodes. Data collected by RFID sensors on visitor badges is stored on mini-computers placed in exhibition rooms and then transmitted to a remote database after a preset time frame. Utilizing MapReduce for data analysis and a leader election algorithm for fault tolerance, this middleware showcases its viability through metrics, demonstrating applications like swift prototyping and accurate validation of findings. Despite using simpler hardware, its performance matches resource-intensive methods involving audiovisual and AI techniques. This design’s innovation lies in its fault-tolerant, distributed setup using budget-friendly, low-power devices rather than resource-heavy hardware or methods. Successfully tested at a historical building in Greece (M. Hatzidakis’ residence), it is tailored for indoor spaces. This paper compares its algorithmic application layer with other implementations, highlighting its technical strengths and advantages. Particularly relevant in the wake of the COVID-19 pandemic and general monitoring middleware for indoor locations, this middleware holds promise in tracking visitor counts and overall building occupancy.

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Section: Introductionmentioning

confidence: 99%