Brick Links

In this study, we examine the influence of weather on daily sales in brick-and-mortar retailing using empirical data for 673 stores. We develop a random coefficient model that considers non-linear effects and seasonal differences using different weather parameters . In the ex-post analysis us

Project Title

Brick Links

Project Area of Specialization

Computer Science

Project Summary

1. We provide a brinks digital platform.In this platform we connect all bricks companies in our country. Our aim to provide bricks in low rate and 100% quality ensure.
2. In the market, therate of bricks is too much expensive so using our application we are offering the best prices as compare to retailer because retailer take commission, if the brick price 7rupees so retailer sale 10rupees so it’s too much expensive but we just take 4% commission from company. so, we are offering the customer round about 8 rupees per brick.
3. There are many types of qualities of bricks so customer doesn’t know about quality we ensure that the quality must be good.
4. When consumer purchase bricks, the consumer or company take too much time of delivery so using our platform, we provide consumersorder as soon as possible.
5. So many consumers would not know about the rate of bricks in which month is less then whole year. In our platform, we guide the consumers about rate of bricks. So, consumers save a large amount of money from bricks.
6. If you want to design to your building map, so architecture demands you 40k to 50k rupees of building map. But we are providing your building design or map in 10k rupees only.
7. As many construction workers (Mistry) who don’t have any idea to calculate bricks and they usually orders less bricks according to your building. So, when you again order of bricks it is possible to increase the price of bricks. Then it is expensive for consumers.So, we know consumers need. We also calculate brinks according to your building design or map, so thatthey save your money.

Project Objectives

• In the market, therate of bricks is too much expensive so using our application we are offering the best prices as compare to retailer because retailer take commission, if the brick price 7rupees so retailer sale 10rupees so it’s too much expensive but we just take 4% commission from company. so, we are offering the customer round about 8 rupees per brick.
• There are many types of qualities of bricks so customer doesn’t know about quality we ensure that the quality must be good.
• When consumer purchase bricks, the consumer or company take too much time of delivery so using our platform, we provide consumersorder as soon as possible.
• So many consumers would not know about the rate of bricks in which month is less then whole year. In our platform, we guide the consumers about rate of bricks. So, consumers save a large amount of money from bricks.
• If you want to design to your building map, so architecture demands you 40k to 50k rupees of building map. But we are providing your building design or map in 10k rupees only.
• As many construction workers (Mistry) who don’t have any idea to calculate bricks and they usually orders less bricks according to your building. So, when you again order of bricks it is possible to increase the price of bricks. Then it is expensive for consumers. So, we know consumers need. We also calculate brinks according to your building design or map, so that they save your money.

Project Implementation Method

• Price Prediction:

In this study, we examine the influence of weather on daily sales in brick-and-mortar retailing using empirical data for 673 stores. We develop a random coefficient model that considers non-linear effects and seasonal differences using different weather parameters

. In the ex-post analysis using historic weather data, we quantify the explanatory power of weather information on daily sales, identify store-specific effects and analyze the influence of specific sales themes. We find that the weather has generally a complex effect on daily sales while the magnitude and the direction of the weather effect depend on the store location and the sales theme.

The effect on daily sales can be as high as 23.1% based on the store location and as high as 40.7% based on the sales theme. We also find that the impact of extreme bad and good weather occurrences can be misestimated by traditional models that do not consider non-linear effects. In the ex-ante analysis, we analyze if weather forecasts can be used to improve the daily sales forecast.

We show that including weather forecast information improves sales forecast accuracy up to seven days ahead. However, the improvement of the forecast accuracy diminishes with a higher forecast horizon.

• Weather Prediction:

To successfully build during periods of extreme weather conditions, designers and contractors use knowledge of local meteorological conditions, as well as historic climatological information for a given area.

During project planning, designers are concerned with climatological data such as the average and extreme daytime and nighttime temperatures or average wind velocity for use in designing mechanical or structural systems.

Contractors, however, are more concerned with meteorological conditions during construction, such as hourly temperatures and mean daily temperatures, as well as the predicted temperatures and wind velocities for the next few days.

Mean daily temperature is determined by adding together the maximum temperature for each day (24 hours, midnight to midnight) and the minimum temperature for the same day and dividing by 2. The term “ambient temperature” as used in this Technical Note is the outdoor temperature at the time considered

• Bricks Calculation

Bricks detection is a computer vision technique that allows us to identify and locate Bricks in an image. With this kind of identification and localization, Bricks detection can be used to count Bricks in a scene and determine and track their precise locations, all while accurately labeling them.

Imagine, for example, an image that contains a lot of bricks. Bricks detection allows us to at once classify the types of things found while also locating instances of them within the image.

Benefits of the Project

• Quality Ensues:

Bricks are undoubtedly amongst the most commonly used construction materials anywhere. Incidentally, concrete is regarded as the most used construction material in the world in terms of weight or volume according to some estimates.

• Low Rates:

Availability at wholesale Rate.

•  Time Saving:

We Make Digital Platform for Bricks Sale and Purchases as Every Person c

Can give the order at digital platform and deliver at doorstep. So, there is

No wastage of time. So, time is saved.

• Easy to order:

Digital Platform Make it easy to order bricks.

• Order your door step:

       Your Delivery at your doorstep just go on digital platform and receive the

Order at doorstep.

• Generate Map.

The Possible Map Generated according to required area.

• Calculate Bricks.

Calculation Bricks according to the map selected by the Customer.

• Price Prediction.

  Price Prediction According to different Weather and Give the Observation

About the Construction Budget.

• Weather Prediction

Technical Details of Final Deliverable

All communication between customers and bricks company must be via the wireless internet protocol and encrypted Because customers can order the bricks easily.

There is no any restriction just using internet, they can communicate to each other.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Core Technology

Others

Other Technologies

Sustainable Development Goals

Industry, Innovation and Infrastructure

Required Resources

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