• Sayera Nazneen
• Ajith Krishna
• Samuel Finney
• Rahul Tata
• Hyma Birudaraju

Acurate Pill identification and detection is important in the context of substance abuse prevention, especially for monitoring the misuse of prescription medications and illicit drugs. Identifying and tracking specific pills can help prevent drug diversion, addiction, and overdose deaths.Traditional methods of pill detection often rely on manual inspection, which can be time-consuming, error-prone, and inefficient.Effective pill detection and identification require specialized training, expertise, and experience, particularly in forensic science and pharmaceutical analysis. Not all individuals possess the necessary skills to accurately identify pills, leading to potential errors and inconsistencies.We propose a comprehensive image analysis pipeline that leverages Machine Learning algorithms like MobileNet V2 to identify and classify pills accurately. We extract relevant features from the images, including color, texture, and shape characteristics, these features are then used to train machine learning models . Leveraging MobileNetV2 for pill detection and identification offers the advantages of computational efficiency, low memory footprint, and real-time inference capabilities, making it an excellent choice for applications requiring mobile deployment. With proper training and fine-tuning, MobileNetV2 can achieve accurate and reliable results, contributing to enhanced patient safety, medication adherence, and healthcare outcomes. Machine learning models offer a promising solution by automating these processes, improving accuracy, efficiency, and scalability, and enhancing patient safety, medication adherence, and public health outcomes.

Pill detection, Machine Learning models, drug recognition, image processing, Pill identification,CNN.

"Employing Deep Neural Networks for Accurate and Efficient pill Idenfication", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.g1-g5, May-2024, Available :http://www.jetir.org/papers/JETIR2405601.pdf

"Employing Deep Neural Networks for Accurate and Efficient pill Idenfication", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppg1-g5, May-2024, Available at : http://www.jetir.org/papers/JETIR2405601.pdf