The use of mobile application technologies and smart devices in the health sector has improved a lot. In this sense health monitoring has evolved using Internet of Things. Nowadays the food habits are changed because of our machine life. This paper mainly focuses on the problems occurring related to health because of food habits. This paper gives the idea for solving this problem by collecting the attributes from the human body. The attributes like cholesterol, calories, glucose, pulse, weight, Body Mass Index, water level, temperature are to be collected from the person by fixing the wearable sensor devices in the human body. After getting these attributes the analysis should be done with the existing database for giving the food recommendations. The food intake level is analyzed for providing health factors. The aim of the paper is to provide the architecture for healthy food recommendations to the persons using sensor data to the person’s mobile application.

Search engines provide ranked information based on the query given by the user. Understanding user search behavior is an important task for satisfaction of the users with the needed information. Understanding user search behaviors and recommending more information or more sites to the user is an emerging task. The work is based on the queries given by the user, the amount of time the user spending on the particular page, the number of clicks done by the user particular URL. These details will be available in the dataset of web search log. The web search log is nothing but the log which contains the user searching activities and other details like machine ID, browser ID, timestamp, query given by the user, URL accessed etc., four things considered as the important: 1) Extraction of tasks from the sequence of queries given by the user 2) suggesting some similar query to the user 3) ranking URLs based on the implicit user behaviors 4) increasing web page utilities based on the implicit behaviors. For increasing the web page utility and ranking the URLs predicting implicit user behavior is a needed task. For each of these four things designing and implementation of some algorithms and techniques are needed to increase the efficiency and effectiveness.