Abstract: Side-hustles, or income-generating work performed alongside full-time jobs, have grown significantly in popularity as the gig economy provides opportunities for supplementary work. This increasing demand has created the need for platforms like AuraAssign, designed to connect individuals seeking temporary jobs with organizations requiring a flexible workforce. Events such as weddings, festivals, and corporate gatherings often require temporary staffing, but traditional systems relying on spreadsheets and static databases fail to meet these dynamic needs, leading to inefficiencies and missed opportunities. AuraAssign addresses these challenges by integrating advanced geolocation technologies and algorithms. The platform utilizes the Haversine formula to calculate precise distances between job seekers and employers and employs the OSRM algorithm (Open Source Routing Machine) with a multi-level A* algorithm to optimize routing, ensuring efficient navigation to job locations. Additionally, AuraAssign incorporates Location-Based Services (LBS) to provide real-time recommendations tailored to user preferences, including location, skills, and availability. It overcomes the limitations of traditional recommendation systems, such as collaborative filtering, which are unsuitable for dynamic and event-based social networks. By streamlining job matching and addressing challenges in short-term workforce management, AuraAssign not only improves user experience but also supports societal needs, offering students supplementary income opportunities to bridge financial gaps.
Keywords: Event-based Social Network, Haversine, Location-Based Service, Open Source Routing Machine.
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DOI:
10.17148/IJARCCE.2025.14581
