KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS VOL. 11, NO. 6, Jun. 2017 2910 Copyright ⓒ2017 KSII Diet-Right: A Smart Food Recommendation System Faisal Rehman 1,* , Osman Khalid 1 , Nuhman ul Haq 1 , Atta ur Rehman Khan 2 , Kashif Bilal 1 , and Sajjad A. Madani 1 1 Department of Computer Sciences, COMSATS Institute of Information Technology Abbottabad, Pakistan [e-mail: frehman, osman, nuhman, kashifbilal, madani @ciit.net.pk] 2 College of Computer & Information Sciences, King Saud University Riyadh, Saudi Arabia [e-mail: dr@attaurrehman.com] *Corresponding author: Faisal Rehman Received October 21, 2016; revised January 2, 2017; accepted February 14, 2017; published June 30, 2017 Abstract Inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to lack of concise information about healthy diet, people have to rely on medicines instead of taking preventive measures in food intake. Due to diversity in food components and large number of dietary sources, it is challenging to perform real-time selection of diet patterns that must fulfill one’s nutrition needs. Particularly, selection of proper diet is critical for patients suffering from various diseases. In this article, we highlight the issue of selection of proper diet that must fulfill patients’ nutrition requirements. To address this issue, we present a cloud based food recommendation system, called Diet-Right, for dietary recommendations based on users’ pathological reports. The model uses ant colony algorithm to generate optimal food list and recommends suitable foods according to the values of pathological reports. Diet-Right can play a vital role in controlling various diseases. The experimental results show that compared to single node execution, the convergence time of parallel execution on cloud is approximately 12 times lower. Moreover, adequate accuracy is attainable by increasing the number of ants. Keywords: Recommender System, Food, eHealth, ACO, Cloud Computing, Pathological Reports A preliminary version of this paper appeared in IEEE ICC 2009, June 14-18, Dresden, Germany. This version includes a concrete analysis and supporting implementation results on MICAz sensor nodes. This research was supported by a research grant from the IT R&D program of MKE/IITA, the Korean government [2005-Y-001-04, Development of Next Generation Security Technology]. We express our thanks to Dr. Richard Berke who checked our manuscript. https://doi.org/10.3837/tiis.2017.06.006 ISSN : 1976-7277