Smart Location Base Services

Whenever we are travelling or go to some new place or need some service or product at our door step at any location at any time. There are so many issues we face when we are at some new location because we are not familiar with the area and the service or product provider there. We do not know which

Project Title

Smart Location Base Services

Project Area of Specialization

Artificial Intelligence

Project Summary

Whenever we are travelling or go to some new place or need some service or product at our door step at any location at any time. There are so many issues we face when we are at some new location because we are not familiar with the area and the service or product provider there. We do not know which service provider or product provider is near. There are always trust issues as we do not know the person who is providing us service. There always a thought that may be someone could steal us.

Moreover, even if there are no trust issues with the service/product provider, he may charge us more than the standard rates as we do not have any other choice and we do not know anyone else at that particular area. Some service/product providers are not good at work and that charge us very high and do not provide quality service/product. In short, we do not know if he can provide us quality service/product with standard rates and we can even trust that service/product provider.

Here we come with the solution of problem. We are developing an Artificial intelligence-based application that will tackle with all of these problems. We are developing an application named as SLBS (Smart Location Based System).

So, what this app is going to do? It will provide a platform to the users and service providers. SLBS will recommend you all the registered trustworthy services/products provider nearest to your current location. No matter where you are? And what the time is? You can just search for the service/product and SLBS will recommend you the list of nearest service providers with their rates, distance and response time. One can also check the feedback or star rating of the service/product provider in order to clear all the doubts which one is best for him. The best part is, every service/product provider will charge you the standard rates. Every service/product provider is registered, so you can trust him. Quality work is the main key to join the SLBS platform for all the services/products provider as it is enabling more opportunities for service provider to increase their customers.

SLBS integrate features like recommended service/product plus ratings and distance from location, list of available service, profile Page, filter list based on location, services listing, messaging and call service, view the location of the service/product on a map, view and add reviews for the service/product, search by postcode and service/product names by text or audio, change which recommender system filtering type to use, choose service/product preferences for the recommender system, use a pinlock to secure the application.

Project Objectives

SLBS also have objective is to solve the problem of finding service/product provide by best persons. SLBS provides you thousands of trusted person that already provide thousands of services with best customer reviews. The main goals of SLBS is to improve user comfort and make daily life easier.

To overcome the problems of any service that is required at any place by any person like at indoor (home), outdoor at any other place. To overcome the problems of household services like cleaning, electrician, plumber need etc. To overcome the outdoor problems like need of car mechanics, problem of food service, problem of fuels and much more. To overcomes the problems that people faces during shopping of goods. To overcome any service that you are looking for but you don’t know where you find that or avail it. SLBS provides you the solution to all of this.

Another important objective of SLBS is to make easier for our users to find any services/products on our app easily with user friendly UI. We provide attractive and simple Design that make our app more easy to use by anyone.

Project Implementation Method

We are Implementing Google Map, Location tracking using (GPS) and Collaborative Filtering (CF) for recommendation. For tracking location we (GPS) and use collaborative filtering (CF) technique for recommender systems. We use general one because our system predicts on people information. General one: In the more general sense, collaborative filtering is the process of filtering for information or patterns using techniques involving collaboration among multiple agents, viewpoints, data sources, etc. Applications of collaborative filtering typically involve very large data sets. Collaborative filtering methods have been applied to many different kinds of data including: sensing and monitoring data. Such as in mineral exploration, environmental sensing over large areas or multiple sensors; financial data, such as financial service institutions that integrate many financial sources; or in electronic commerce and web applications where the focus is on user data, etc. The remainder of this discussion focuses on collaborative filtering for user data, although some of the methods and approaches may apply to the other major applications as well. We are applying two methods in collaborative filtering first one is look for users who share the same rating patterns with the active user (the user whom the prediction is for).Second use the ratings from those like-minded users found in step 1 to calculate a prediction for the active user Example: Amazon is known for its use of collaborative filtering, matching products to users based on past purchases. For example, the system can identify all of the products a customer and users with similar behaviors have purchased and/or positively rated.

We are Implementing Agile Model. Since the Agile app development methodology consists of a few short cycles (2–3 weeks each), there is risk minimization. A customer can see the result after each cycle, and he/she can request to make any changes. Thus, a customer has a direct influence on the development and he/she controls it. Each Agile application development lifecycle includes the following stages:

One cycle isn’t enough for building a full-fledged product, but each iteration shows part of the functionality that can be tested and/or changed. After each cycle, the development team sums everything up and can receive new requirements, then some adjustments can be made in the software development plan.

Our system is new so we will be using direct implementation. We will also do phased and pilot implementation on our premium users and service providers. We are targeting every smart phone user in Pakistan.

Benefits of the Project

SLBS mainly provides the services/products at your current location. Users can avail all types of home services at their doorstep and outdoor services at any place. Users can buy all types of goods at their doorstep with just one click. You can get anything, any service of any type by shifting on our platform. The smart UI design of our app enable users to use app easily. The smart location service of our app gives you the optimal result on your search. Our trustworthy service providers gives you professional services. The rating and reviews of each service provider give you a clear view of that provider that makes your selection better. We are providing the stander rates according to the market. Our platform is enabling more opportunities for service provider to increase their potential customers. Overall it is a complete application for anyone for everything.

Technical Details of Final Deliverable

For tracking location we (GPS) and use collaborative filtering (CF) technique for recommender systems. We use general one because our system predicts on people information. General one: In the more general sense, collaborative filtering is the process of filtering for information or patterns using techniques involving collaboration among multiple agents, viewpoints, data sources, etc. Applications of collaborative filtering typically involve very large data sets. Collaborative filtering methods have been applied to many different kinds of data including: sensing and monitoring data. Such as in mineral exploration, environmental sensing over large areas or multiple sensors; financial data, such as financial service institutions that integrate many financial sources; or in electronic commerce and web applications where the focus is on user data, etc. The remainder of this discussion focuses on collaborative filtering for user data, although some of the methods and approaches may apply to the other major applications as well. We are applying two methods in collaborative filtering first one is look for users who share the same rating patterns with the active user (the user whom the prediction is for).Second use the ratings from those like-minded users found in step 1 to calculate a prediction for the active user Example: Amazon is known for its use of collaborative filtering, matching products to users based on past purchases. For example, the system can identify all of the products a customer and users with similar behaviors have purchased and/or positively rated.

SLBS integrate features like recommended service/product plus ratings and distance from location, list of available service, profile Page, filter list based on location, services listing, messaging and call service, view the location of the service/product on a map, view and add reviews for the service/product, search by postcode and service/product names by text or audio, change which recommender system filtering type to use, choose service/product preferences for the recommender system, use a pinlock to secure the application.

SLBS enabled the functionalities like it tracks the users location and sends the data to the server and then displays the recommended service/product to the user, security (only user id and address will only be shared to the seeker), send message via online messaging service API, unique Id generator for seeker and recruiter, OTP Validation for seeker and recruiter, change Password by reset link.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Others

Core Technology

Artificial Intelligence(AI)

Other Technologies

Blockchain, Others, Big Data, Clean Tech

Sustainable Development Goals

No Poverty, Decent Work and Economic Growth, Industry, Innovation and Infrastructure, Responsible Consumption and Production

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com