Review of Object Detection Techniques and AI-Driven Recipe Generation for Smart Kitchens

Review of Object Detection Techniques and AI-Driven Recipe Generation for Smart Kitchens

Melgibson Shiju
Department of Computer Science (Cyber Security)

Vimal Jyothi Engg. College Chemperi, Kannur melgibson.nj@gmail.com

Mathew George
Department of Computer Science (Cyber Security)

Vimal Jyothi Engg. College Chemperi, Kannur mathewgeorge942@gmail.com

Navaneeth AS
Department of Computer Science (Cyber Security)

Vimal Jyothi Engg. College Chemperi, Kannur navaneeth2022appus@gmail.com

Muhammed Sinan PT
Department of Computer Science (Cyber Security)

Vimal Jyothi Engg. College Chemperi, Kannur ptssinan@gmail.com

Sr. Reema Jose
Dept. of Computer Science (Cyber Security)

Vimal Jyothi Engg. College Chemperi, Kannur srreemajose@vjec.ac.in

Abstract—The integration of object detection and conversa- tional AI in smart kitchen systems presents a promising avenue for enhancing cooking convenience. This review explores object detection techniques for identifying available ingredients and their application in generating personalized recipe suggestions. The system leverages computer vision to detect and catalog kitchen items and employs conversational AI to engage with users and recommend recipes tailored to their preferences, dietary restrictions, and available ingredients. By combining advanced object detection methods with natural language processing mod- els for dynamic recipe generation, the system aims to provide an intuitive user experience, some key challenges includes real- time performance, website integration, and personalization, are addressed, offering insights into the development of intelligent cooking assistants that bridge the gap between AI and daily life. Index Terms—Smart Kitchen Systems, Object Detection, Con- versational AI, Computer Vision, Natural Language Processing (NLP), You Only Look Once(YOLO), Single Shot Detector(SSD),

Deep Neural Networks (DNNs)