People counting system for retail analytics using edge AI
This work addresses retail store optimization by enabling conversion rate analytics, but it appears incremental as it applies existing edge AI methods to a specific domain without major innovations.
The paper tackled the problem of retail conversion rate measurement by developing a cost-effective people counting system using edge AI, which calculates conversion rates by counting store visitors and transactions to provide analytical insights with minimal hardware requirements.
Developments in IoT applications are playing an important role in our day-to-day life, starting from business predictions to self driving cars. One of the area, most influenced by the field of AI and IoT is retail analytics. In Retail Analytics, Conversion Rates - a metric which is most often used by retail stores to measure how many people have visited the store and how many purchases has happened. This retail conversion rate assess the marketing operations, increasing stock, store outlet and running promotions ..etc. Our project intends to build a cost-effective people counting system with AI at Edge, where it calculates Conversion rates using total number of people counted by the system and number of transactions for the day, which helps in providing analytical insights for retail store optimization with a very minimum hardware requirements.