Android点菜软件-外文及翻译(共22页).doc

精选优质文档-倾情为你奉上毕业设计（论文）原稿及译文译文题目 基于安卓系统的电子菜单软件 原稿题目 Intelligent e-Restaurant using Android OS 原稿出处International Conference & workshop on Advanced Computing 2013 (ICWAC 2013) Intelligent e-Restaurant using Android OSABSTRACT：The simplicity and ease of access of a menu are the main things that facilitate ordering food in a restaurant. A Tablet menu completely revolutionizes the patrons dining experience. Existing programs provide an app that restaurants can use to feed their menus into IOS & Android based tablets and make it easier for the diners to flip, swipe & tap through the menu. We here aim to provide the restaurants with a tablet menu that would recommend dishes based on are commendation algorithm which has not been implemented elsewhere. In addition to this we run the app on an Android based tablet & not on an IOS based tablet which is more expensive alternative. We use a cloud-based server for storing the database which makes it inexpensive & secure.Keywords：Recommendation, Tablet, Application, Restaurant Menu, Intelligent, Android1. INTRODUCTIONOver the years, technology has tremendously revolutionized the restaurant industry. But much of the innovation has been with point-of-sale (POS) operations. Yet other areas of a restaurant are ripe for innovation, such as the menu. Traditional restaurant service requires waiters to interact with customers directly before processing their orders. However, a high-quality recommendation service system would actively identify customers and their favorite meals and expenditure records. There is a famous saying that “People eat with their eyes”. The e-Menu provides additional information about menu items and drinks than a traditional paper menu. With interactive pictures it gives additional information about the food item. Tablets are said to eliminate order-taking errors from the waiters. In the kitchen, there is less confusion as everything is now written clearly. Developers of similar applications maintain that customers who seat at tables outfitted with tablets spend about 20% more than those at other tables. With the visuals, you know exactly what youre going to get in your plate. The service goes quicker. Tablets are said to allow cutting the labor expenses. Customers feel more involved in the process. Restaurants can build their e-reputation and customer community in live.The restaurant menu has evolved from its humble beginnings on carte chalkboards and imageless print to todays detailed, colorful displays. With the emergence of digital tablets and user-friendly touch screen technology menus can move to a whole new surface. With this electronic menu, orders can be taken correctly the first time. There is no need to run back and forth to a distant terminal, because the terminal is always with the server. Every order is associated with an individual seat at the table, and orders are built one customer at a time, just like on paper, but with greater accuracy. Items can also easily be shared by the whole table, moved or modified, and noted and the cost can be calculated in real time.The Recommendation algorithm suggests dishes to the patrons based on previous orders. It makes it easier for the customer to build his/her order and also view the most popular dishes. Moreover, various dimension filters can be used according to individual preferences e.g. Price, taste, quantity, etc.There are several restaurants in Mumbai which have replaced the traditional paper menus with the digitized tablet menu. But none of the apps let the patron place an order directly to the kitchen. The tablets use is restricted to simple viewing of the menu.2. EXISTING SYSTEMS2.1 Conventional SystemsRestaurant services such as making reservations, processing orders, and delivering meals generally require waiters to input customer information and then transmit the orders to kitchen for meal preparation. When the customer pays the bill, the amount due is calculated by the cashier.Although this procedure is simple, it may significantly increase the workload of waiters and even cause errors in meal ordering or in prioritizing customers, especially when the number of customers suddenly increases during busy hours, which can seriously degrade the overall service quality.2.2 Electronic POS TerminalsA very commonly implemented system, currently being used by numerous restaurants and chains all over the world, is the electronic point-of-sale terminal system. Here, the servers/waiters generally take the order from the customer and head onto a terminal, where they can feed the order into a computer. The order can then be transmitted to the kitchen automatically via the terminal through a network, or it may even be delivered manually by the server to the kitchen.Although a huge improvement over the pen and paper still prevalent over the world, this does not have much value addition for the customer and mostly only benefits the establishment and the administration of the establishment.2.3 Tablet Based MenuWith the current onslaught and popularity of touch based devices, especially the Apple iPad, it did not take long for the tablet based menus to make an entrance in to the market.In their current state, these menus are just a glorified version of their paper based counterparts.The workflow, even with these tablet menus, remains the same as the one mentioned in section 2.1 or a combination of the previous two. There is very little value addition to the customer and the establishment or its staff.The available technology is definitely not being utilized to its maximum potential.3. PROPOSED SYSTEM3.1 System ArchitectureThe following figure (Fig3.1), demonstrates the basic architecture of our system. Understanding the other intricacies and details of the system will become a lot easier if one goes through this figure, before diving into the rest of it.Fig 3.1 Basic System Architecture and System ComponentsThe system will consist of the following components: The backend, which is made up of the web server and the database, and the frontends that include both the patron frontend (delivered as a native mobile application) and the administration or the kitchen frontend (delivered as a web application).This system is based on the very popular Model-View-Controller (MVC) architecture. MVC is most commonly used in websites, very popular and tried and tested.None of the frontends directly “talk” to the database. They instead rely on RESTFUL web services that can be used to perform CRUD operations on the database.Fig 3.2 FlowchartThe following figure (Fig 3.2) demonstrates the flow of our tablet application.3.2 System OverviewThe most important components of this system are the database and the patron frontends or the tablet applications.Providing value to both the business and its patron is an important objective, but we believe that one follows the other. Following that belief, the customer is given a whole lot of importance.The patron will be presented with a tablet, running the Android OS. This tablet will be synchronized with the database running on our centralized cloud powered servers.The menu data, upon synchronization, is stored on locally on the tablets so that the user, i.e. patron, need not wait for the menu to be downloaded from the servers. This will allow faster access to the menu.The user can then browse the menu however they want to, sorting the items on various dimensions like price, popularity, ratings, etc. The user can also click through to view more information about any item like nutritional information, ingredients, trivia and any other content that the restaurant administration may feel like including.The user can also view personalized recommendations for items that they may like. This is one of the most important aspects of our system that not only enhances the customer experience but can also help increase revenue for the business.While browsing through the menu, the customer may add items to his/her order. This process is commonly known as “building the order”. After the order is built and read, the user may go ahead and place the order. The staff will automatically and almost instantly be notified about the new order so that they can act on it.If the establishment allows, the user may even track the status of their order so that they know when to expect their food and drinks to land up on their table.3.3 Recommendation OverviewThe recommendation algorithm is an innovative feature that we aim to include in our menu. When most tablet menus provide the customers with only a simple menu, this system will provide recommendations which will make it easier to build an order considering what other customers have ordered previously or the similarities between various dishes.Recommendation systems using sets were considered . We finally decided to use the below methodology, which has been discussed in an earlier study. The algorithm mainly has 5 parts:1. Users - a certain number of people are made to rate individual food items. 2. Entities - the food items.3. Value Dimensions - the categories that are formed to rate the food items e.g. Price, quality, meat content, etc.4. Belief System - is personal to each user & allows telling the system what ideal value they want each value dimension to have.5. Ideal candidate - set of ideal value dimensions that are formed on the basis of a weighted average.Each User rates a food item on a scale of 1 to 5 with respect to two things:1. Users ideal value dimension.2. The weight or the importance of that value dimension.With the food items set in place, our next task was to analyze the various attributes that were associated with each food item. We applied a food item click counter to the entire data set, which produced a list of the most viewed food item. After listing out the Top N clicked food-items by the customers, we apply normalization to the retrieved list of food-items, to filter out redundant clicks.We further investigate the levels of commonality that existed between various pairs of food items. Jaccards co-efficient was used to calculate the degree of similarity.The Jaccard index, also known as the Jaccard similarity coefficient (originally coined coefficient de communaute by Paul Jaccard), is a statistic used for comparing the similarity and diversity of sample sets.The Jaccard coefficient measures similarity between sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets: Collaborative filtering-based recommender systems rely on information derived from social activities of the users, such as opinions or ratings, to form predictions or produce recommendation lists. Existing collaborative filtering techniques involve generating a user-item matrix, from which recommendation results could be derived Content-based ltering focuses on the selection of relevant items from a Content-based ltering focuses on the selection of relevant items from a large data set, things that a particular user has a high probability of liking. This involves training the data set with machine learning techniques. Clustering involves sectioning the data set into particular sets, each of which corresponds to certain preference criteria. Also, typical recommendation systems output their results either as predictions, a numerical ranking value corresponding to a particular item or recommendations, a list of relevant items .The conventional approaches to computing similarity involve the use of two popular techniques: Pearson correlation & Cosine EquationWe used Jaccards coefficient in our models. 3.4 TechnologiesThe technologies being used to build the system are cutting and largely open source. Open source technologies help in keeping the costs in check, thus enabling the various establishments to use this setup without any cause of concerns with regards to the costs involved.Amazon Web Services has a very effective and inexpensive service known as Elastic Cloud Compute which allows one to setup servers on the fly with the specifications one requires. We will be using the same (or similar) service to keep the costs down and maintain scalability. The server uses software known Nginx. Nginx engine x is an HTTP and reverse proxy server, as well as a mail proxy server, written by Igor Sysoev. For a long time, it has been running on many heavily loaded Russian sites including Yandex, Mail.Ru, VKontakte, and Rambler. According to Netcraft nginx served or proxied 12.81% busiest sites in February 2013.The database uses the ever popular MySQL as its DBMS. The web services mentioned earlier are powered by a web framework called Symfony that uses PHP and an ORM called Doctrine. OAuth and SSL can and will be used to implement security.The tablets supplied to the patrons will be running Android OS.3.5 Comparison of Existing vs. Proposed systemsTable 3.1 Comparison of SystemsExisting SystemProposed SystemOperating SystemsIOSAndroidCommunication ChannelCommunication between the customer & the waiterCommunication between customer & the terminalCustomer identificationRFID used to identify customers Additional hardware requiredUser accounts maintained in the database serverServer locationLocalized serverCentralized serverRecommendation SystemRecommendations not implementedRecommendations implementedExclusivityExclusive to every establishmentCan be extended to be used by multiple establishments3.6 Feature OverviewIn this section we wont go into the detailed features of the system, but instead take a birds eye look at the same.3.6.1 Intuitive, Beautiful & User friendlyThe end users, i.e. the restaurant customers, will have maximum interaction with this system. This interaction will mostly occur through the tablet application.Unlike most applications that have a targeted user base, our application will be used by all & sundry. It could be used by an 8 year old or an 80 year old person, from varying cultures and background. This ensures the need for a design that is intuitive, user friendly and beautiful thus making it a pleasure to use.3.6.2 ScalableThe system has the potential of being used by millions of users at any given time, with possible peaks at various rush hours at the establishments this may be implemented at. Thus, the system will have to be scalable and should be able to accommodate as many users and as much data as required.3.6.3 SecureSince private information about so many businesses and individuals will be stored in our database. We will need to ensure that the whole system - the web service, the app, the database as well as the server be secure from external as well as int