IOT Solution for Vehicle Maintenance and Report Generation System

INTRODUCTION

  • Many automotive manufacturers are now moving towards an IoT platform for manufacturing and for service purposes.
  • The main advantages of using IoT in cars are Optimized maintenance and logistics.
  • Our idea is to monitor vehicle status (fuel, efficiency/Km, battery, oil levels, etc..,.) to the customer as well as the manufacturer.

CONCEPT

  • The main aim of every car manufacturer is to increase the life of the car and it’s crucial to maintain the car in a good condition to achieve it.
  • Many problems in vehicles arise due to improper maintenance. Many lose track of their service status and it’s a tiring process to keep in touch with every customer in a large automotive industry.
  • If we maintain a system, that automatically updates the vehicle’s conditions periodically to a specified server, and the system will generate a report, that will be forwarded to the customer and the service team, a lot of manual work will be removed.
  • We as a team provide an IoT solution for vehicle maintenance and report generation system.

FLOW DIAGRAM-FUNCTIONAL DECOMPOSITION

  • Our Vehicle Maintenance and Report Generation system collects data from the sensors available in the car itself and reports it to a transceiver module(ESP8266) which is connected to a database in the cloud.
  • when new data is updated/inserted into the table an event is triggered. This event updates the information in the dashboard, which will be displayed to the customer and manufacturer.
  • Then a weekly/monthly/yearly report generation event is triggered, which will mail the report to the specified recipient.

FUNCTIONAL DECOMPOSITION

Data collection:

The data is collected from the sensor stream of the car. This data is redirected to the ESP8266 module. The ESP8266 is connected to the server, that is allotted to the car. The ESP8266, when all data is collected, converts it into a JSON file. Then the server sends a post request to the server.

Event trigger:

Many database servers provide pl/SQL-based triggers. Here an Update and Insert trigger is created for the table. Oracle server provides a wide range of PL/SQL functions. The IP of ESP8266 is connected to the oracle server, which on periodic updates in the table triggers an event.

Dashboard:

The dashboard is created using HTML and CSS and deployed in the cloud using the NODE JS framework.

FUNCTIONAL SPECIFICATION

Hardware:

ESP8266 CP2101 module(CAR)
ESP8266 CP2101 module(HOME)

Programming Language:

SQL
Javascript (Node JS)
C++(Arduino .ino)
HTML CSS

Dashboard

The Vehicle Maintenance and Report Generation System dashboard are developed using Adafruit.io. This website provides dashboard development for MQTT-based devices

Bus Reservation System or Online Bus Ticket Booking Java Project

Purpose of the Project:

This project is meant to delineate the features of Online Bus Ticket Booking, so as to serve as a guide to the developers on one hand and a software validation document for the prospective client on the other. The Bus Reservation System is developed for Travellers to reserve seats online and to save them from hassles. It will allow the passengers to enjoy the booking of bus tickets from the present position through the internet. They will be provided with the bus routes along with some other facilities like booking the tickets based on their comfort level, the time of arrival and departure, and canceling the tickets. The administrator can handle various aspects like applying the offers, changing the facilities according to price, can monitor various other things. The Travel Agency can also use this application for managing their ticket booking service.

Scope of Project

This Bus Ticket Booking application can be used by any Travel Agent to issue tickets to customers. It also helps the customer to enquire about the availability of seats in a particular bus at a particular date from a particular location. It will also provide the facility to check the timings and schedule of the buses along with the ticket price.

Aim & Objective of the Project

  • Up To Date information is provided that is not possible manually.
  • The objective of my project is to make the Ticket Booking system of an Agency, simple, reliable, user-friendly, and corrective. Moreover less time-consuming as compared to manual work.
  • To Increase The Ticket Booking efficiency.

Features Provided to User

  • The User can enter the sources and destination to view the buses on the specific route.
  • The User can register himself and then re-login to book the tickets.
  • Can check the seats available?
  • Can see all the bus information
  • Can book no. of tickets after registration.
  • Can check the number of Seats already booked.
  • Can view the bus information like arrival time, destination time, etc.

Features provided to Customer

  • The Customer can Update his profile.
  • Can see his Booking.
  • Can change the password.
  • Can Book tickets.

Features Provided to Admin

  • Add the route.
  • Delete the route.
  • Remove the bus from the route.
  • Update the bus details.
  • Update the route details.
  • Add the bus to the specified route.
  • View the Total tickets booked, seats booked, etc.

Functional Requirements:

Activity Diagram for User:

Activity Diagram for Customer:

Activity Diagram of Admin:

Use Case Diagram:

ER Diagram:

List of Actors :

1. Administrator
2. Passengers

Description:

Registration: 

  • Registration if the customer wants to book the bus ticket then he/she must be registered.
  • Unregistered users will not be allowed to access the site.

Login:

  • The passenger who has registered can log in to the system by entering the valid user id and password.
  • If admin logins, they can add or remove bus, can change the price and the timings.
  • If users logins, they can book the ticket from their particular location to their desired destination.

Selection of Source and destination:

The passenger will be able to choose the source and destination.

Available Buses:

After the selection of the source, destination, and date the available buses for the specific route along with the time will be shown to the user.

Bus Route:

The Route to be followed by the bus while traveling from the source to the destination will be shown to the user.

Ticket Booking:

The passenger will be able to book the tickets as per their comfort of price, bus category, time, date, etc.

Logout:

After the payment of the ticket, the customer will be logged out.

Report Generation:

After all transactions, the system will generate the online ticket and will send one copy to the passenger’s Email- address and another one to the system database to maintain the records of the passengers along with the traveling details.

Technical Issues:

  • This Bus Ticket Booking system will work on client-Server architecture. It will require an internet server.
  • The Bus Ticket Booking system should support some commonly used browsers such as Chrome etc.

The customers may select the different options which will be open on another screen as

1. Login Page
2. Registration Form
3. Source and destination (state-wise)
4. Journey Date
5. Search Buses
6. select a pickup and drop location.
7. Offers
8. Route Directories
9. Payment Gateways

Design Constraints:

This Bus Ticket Booking system should be developed using Standard Web Page Development Tool, which conforms to GUI standards such as HTML, XML, JSON, etc.
The system should support various RDMS and Cloud Technologies.

Operational Scenario:

The passenger will log in and will enter the source, destination, and date. The system will show all the buses from that route reaching the entered destination along with the bus type and the seats available for booking along with the fair. The passenger will choose the bus seat according to their comfort and choice. The payment will be done and the online bus ticket will be generated and will be sent to the email address of the user. The user will also be provided with the ticket cancelation option.

Benefits of Online Ticket booking System

  • This system will help to maximize the number of Reservations.
  • Easy to Manage the calendar.
  • Easy to Manage all the records.
  • This System is fully functional and flexible.
  • Easy to use.
  • Saves a lot of time, money, and Labour.
  • This Application acts as an office that is open 24/7.

CONCLUSION

In the Online Bus Ticket Booking system, we have developed a secure, user-friendly Website where users,s or visitors, can view and search the buses for a specific route and can check seats available on the buses. Here we have maintained records of passenger details, seat availability, price per seat, bill generation, and other things, we have developed a computerized reservation system successfully.

Future Scope

  • This Bus Ticket Booking project can be enhanced further by adding the Agent Module to perform the agent-related functionalities, The generated ticket can be sent to the email id of the customer.
  • The website is flexible enough to be modified and implemented as per future requirements.
  • We have tried our best to present this website. Messages and Email alerts for various things can be sent to the Users so that they cannot miss anything.
  • The offers information for various festival seasons can be sent to the User. The payment-related things can be upgraded.

Download the Complete project on Online Bus Booking System Code.

Smart Agriculture System Project on IBM IOT platform using NodeRed framework

Project Scope

We need to follow these steps to complete our Smart Agriculture System Project:

  • Project Planning and Kickoff
  • Explore the IBM Cloud Platform
  • Connect the IoT Simulator To the Watson IOT Platform
  • Configure the Node-red to Get the Data From the IBM IoT Platform And Open Weather API
  • Building A Web App
  • Configure Your Device to Receive The Data From The Web Application And Control Your Motors

Our Project’s main aim is to help farmers to control their motors from home. He/ She can On and Off his motor by using his mobile phone.
By using Weather API he can know the weather conditions like temperature, humidity, and soil moisture.

Project Background:

  • This Smart Agriculture System Project mainly aims to help the farmers to ease their work.
  • Farmers can get real-time weather conditions by using smart agriculture.
  • Instead of physical devices we create devices in the IBM IoT platform and use them in our project.
  • We connect our device to the IBM node in the NodeRed framework.
  • We need to create a Weather API account to configure the weather API Platform.
  • We then Configure our Node-red to get the weather forecasting data using HTTP requests.

Project Schedule:

  • Project Planning and Kickoff
  • Explore IBM Cloud Platform
  • Connect The IoT Simulator To the Watson IOT Platform
  • Configure The Node-red To Get The Data From IBM IOT Platform And Open Weather API
  • Building A Web App
  • Configure Your Device To Receive The Data From The Web Application And Control Your Motors

Project Requirements:

  • IBM Cloud Account and IBM Watson IOT Platform to create device and sensor
  • Python IDE
  • Node-Red
  • Open weather API Platform

Functional Requirements:

  • Measure Temperature.
  • Gauge Temperature.
  • Gauge Humidity.
  • Gauge Pressure.
  • Weather API.
  • Display the sensor readings using the Watson IOT sensor.
  • Respond to sensor readings and send alerts to the user.

Technical Requirements:

IoT Simulator

Software Requirements:

  • Python
  • Node-Red
  • IBM Watson IOT Platform
  • Open Weather API

Project Deliverables:

A Smart Agriculture System web App for farmers where he can:

• Monitor temperature, humidity, and Soil moisture along with weather forecasting details.
• Control motor for watering the crop through the web app from where he was.

THEORETICAL ANALYSIS

  • Required Software Installation
  • Node-Red

Installation:

  • First, install the Node
  • open command prompt
  • Type ->npm install node-red

To Run the application:

  • open command prompt
  • And then type “node-red”
  • Now open http://localhost:1880/ in the browser

Installation of IBM IOT nodes and Dashboard nodes for Node-Red

  • In order to connect to the IBM Watson IOT platform and create the web UI, these nodes are required
  1. IBM IoT Node
  2. Dash Board Node

IBM Watson IOT Platform

  • Steps To Configure:
  • Create an account in the IBM cloud using your email ID
  • Create IBM Watson Platform in services in your IBM cloud account
  • Launch the IBM Watson lot Platform
  • Create a new device
  • Give credentials like device type, device ID, Token
  • Create API key and store API key and token elsewhere

Python IDE

  • Install python 3 Compiler
  • I Installed PyCharm Community Edition 2020

IoT Simulator

 In our project in the place of sensors, we are going to use a lot sensor simulator which gives random readings to the connected

OpenWeather API

Building Project

Connecting IoT Simulator to IBM Watson IOT Platform

  • Open link Provided in section 4
  • Give the credentials of your device in IBM Watson IoT
  • Click on Connect
  • My credentials given to the simulator are:
  • Organization ID:ka1gns
  • Device Type:nodemcu
  • Device ID:1234five6789
  • Authentication Method:use-token-auth
  • Authentication Token:*********
  • You, Will, receive the simulator data in the cloud
  • You can see the received data in Recent events
  • Data is received in this format (JSON)
  • You can see the received data in cards by creating cards on Boards Tab

4.2    Configuration of Node-Red to collect IBM Cloud Data

  • The Node-Red IBM IoT App is added in Node-Red Work The appropriate device credentials obtained earlier are entered into the node to connect and fetch the device to Node-Red
  • Once it is connected Node-Red receives data from the device
  • Display the data using debug node for

Configuration of Node-Red to collect data from Open weather API

  • The Node-Red also receives data from the OpenWeather API by HTTP GET request. An inject trigger is added to perform HTTP requests for every certain
  • The data we receive from OpenWeather after the request is in JSON format

Configuration of Node-Red to send commands to IBM Cloud

  • By using IBM IoT out Node I used to send data from Node-Red to IBM Watson So, after adding it to flow we need to configure it with the credentials of our Watson device.

Adjusting UserInterface

  • By connecting all the flows shown above
  • We can display our UI by clicking on the dashboard tab in Node-red
  • On the above page, we can display the sensor data and motor
  • On this page, we open weather API data is displayed

Development of Online Shopping Bot using IBM Watson

Introduction

Overview

Online shopping plays a great role in the modern business environment. The best option available for customers in pandemic situations is to use chatbots for online shopping. To support customers in a better way, online shopping bot has opened a door of opportunity and advantage to the firms and customers for having a feel of buying items in a better way. The bot helps to introduce the online shop by listing the items available; it also shows the price of the items and takes orders from the customer. If the customer wishes to see the items, the bot also provides images of the items. This facility ensures the customer sees the products live and gives requests to buy items.

Block Diagram:

Flow Chart Diagram:

Purpose

The online shop bot can help the customer to see the list of items available, images of the images, and the price of the items, and also accepts orders for the items. The purpose of this bot is to save valuable time and money on travel.

  • Literature Survey

In this section, we will discuss the existing solutions available for online shopping and the proposed solution to overcome the limitations.

  • Existing Problems and Solutions

In the past decade, people use the internet as a daily service to access emails, perform online tasks, do shopping, etc. Naturally, people have widely started using the internet at shopper stops too. This showed their willingness to do online shopping. This brings huge responsibility to the shop owners to keep up the buyer’s faith in the particular website. The most important points that affect the customer attitude towards online shopping are customer convenience, collection of information, social contact, and customer diversity.

There are several websites available currently to handle online shopping like Amazon, Flipkart, Big Bazaar, etc. Kotler, (2003) has described the Customer buying method in several sequential steps namely learning, information processing, information searching, evaluating the alternatives, decision making, and post-purchase behavior. When using such websites usability and trust also play a major role and these issues to be handled carefully. With all these facilities available, still we could find some gaps in existing website-based online shopping solutions where the user has limited freedom to communicate or ask doubts regarding items and get a feel of having a discussion with shoppers. This limitation can be overcome by using chatbots for online shopping.

  • Proposed Solution

In recent years, many organizations have shown tremendous interest in developing chatbots for online shopping. These chatbots help customers to handle their queries and to provide information on any kind of items requested. The willingness of the customers to use shopping bots also increased enormously due to the interest in shopping using the internet in pandemic times.

Theoretical Analysis

  • Block diagram
  • Hardware /software requirements
  • Processor: Intel i5
  • Memory: 16GB
  • System Type: 64 Bit Operating system
  • IBM Watson Assistant
  • Node-RED UI Generator

Experimental Investigations

The online shopping bot is developed using IBM Watson. The intents, entities, and context variables are generated, and the JSON file can be downloaded.

Advantages and Disadvantages

  1. An online shopping bot helps to see the list of items available for purchase.
  2. The shopping bot provides the details of the items requested by giving its image and cost.
  3. The shopping bot accepts the mail id to send the order receipt.
  4. The shopping bot accepts the order by asking the item, quantity, and mode of
  5. The shopping bot is interactive.
  6. The shopping bot is simple.
  7. The shopping bot is Usable.
  8. The shopping bot is a user
  9. The shopping bot is available 24/7
  10. The shopping bot is reliable.

Disadvantages

  1. The shopping bot is currently not accepting addresses in the chatbot.
  1. After receiving the receipt, the other interface like email to be used to share the address with the shopper.

Applications

The online shopping bot can be used for advertisement, recommendation, and taking orders from the customer when the customer is living in a chatbot with the shopper.

Conclusion

The online shopping bot is the most useful feature for online shoppers to have a satisfying purchase. With all the possible features embedded in bot it can help the customer to have a successful and satisfactory shopping with less money and time.

Future Scope

  1. The shopping bot can be extended to get reviews
  2. The shopping bot can be added with features like showing offers.
  3. The shopping bot can give recommendations by showing the associated items

Classification of American Sign Language using online RESTful application

  • INTRODUCTION

This document report provides the desired layout to develop an online application service that accepts Human Skeletal key points of a sign video and returns the label of the sign in a JSON response. The document contains information about the extraction of key points from the videos using Tensor Flow’s Pose Net library and four different deep learning models that can classify American Sign Languages into six different signs. i.e {buy, fun, hope, really, communicate, mother}. Moreover, it also contains information about hosting services using flask API on ‘PythonAnywhere’ and steps involving handling HTTP requests coming from different users.

  • TECHNICAL APPROACH

Firstly, we have accumulated all the raw video data sets which have been recorded as a part of Assignment-1 and extracted frames of the particular timeline. Then, we used Tensor Flow’s Pose Net library in order to extract key points from the images, which are considerably used as training data for models. We have tried three different approaches to preprocess data and picked the one which gives the best accuracy for the trained models.

Approach-1: Scaled down raw data using the Universal Normalization technique and extracted a few features like- Standard Deviation, Moving Mean of Window size 5, Zero Crossing Rate, Dynamic Time Warping distance, and built feature matrix. Then we applied PCA on the feature matrix and using K-fold Cross-validation we trained four deep learning models named Convolutional Neural Network, K nearest neighbor, Support Vector Machine, and Random Forest. The average accuracy of the given models lay between 60-65%.

Approach- 2: As a part of the second approach, we expelled some features by observing the movement of each body part in videos for different signs and made a feature matrix of only important features. Then we apply Standard Scaler and Min Max Scaler in order to normalize data and trained our models using the first approach.

Somehow, we were able to increase the average accuracy of the models by 10%.

Approach -3: We have observed in the second approach that, our model is only considering the static coordinates of each body part, so we subtracted each coordinate of different body parts from the static body parts and processed the data in the same manner. So, by doing this approach we got our highest average accuracy which lies between 85% to 90%. 

  • INITIAL FEATURE EXTRACTION 
  1. Zero Crossing Rate
  2. Moving Average Window
  • Standard Deviation
  1. Dynamic Time Warping Distance.

Zero Crossing Rate: The zero crossing rate is the rate of sign- changes along with a signal, i.e the rate at which the signal changes from positive to zero to negative or vice versa. Zero Crossing Rate can be used as a primitive pitch detection algorithm for signal processing.

Moving Average Window: Moving Average is optimal for reducing random noise while retaining a sharp step response. This makes it the premier filter for the time domain encoded signals

Standard Deviation: The standard deviation is a measure of how far the signal fluctuates from the mean. It also depicts how data disperse near the mean of particular data series.

Dynamic Time Warping Distance: DTW measures the similarity between two temporal series data. Any linear sequence data can be analyzed with DTW, it aims at aligning two sequences of feature vectors by warping the time axis iteratively until an optimal match between the two sequences is found.

Feature Engineering:

We have expelled a few features by observing the movement of each body part for different signs and made a feature matrix with only important features. Below is the list of features that we considered for training models.

[“nose_x”, “nose_y”, “leftShoulder_x”, “leftShoulder_y”, “rightShoulder_x”, “rightShoulder_y”,”leftElbow_x”, “leftElbow_y”, “rightElbow_x”, “rightElbow_y”, “leftWrist_x”, “leftWrist_y”,      “rightWrist_x”, “rightWrist_y”]

Here, we observed that the coordinates value of each body part shows a static position for a given time, so we have subtracted each body part’s coordinates value from the corresponding static body part’s coordinates. Here, we have considered “nose”  as a static body part and subtracted each body part with corresponding X and Y coordinates.

The above-mentioned approach would become simpler for the models to understand the movement of each body part, as we have a relative position for each body part, the model can easily predict certain gestures by examining the positive or negative sides of coordinates.

  • MODELS USED:
  1. K nearest neighbor
  2. Convolution Neural Network
  • Support Vector Machine
  1. Random Forest

K Nearest Neighbor: The K Nearest Neighbor classifier is one of the most simple machine learning algorithms that simply relies on the distance feature vectors. It classifies unknown data by finding the most common classes among k nearest examples. The majority vote of the class label is assigned to unknown data. As KNN is a lazy learning algorithm, it works more efficiently when our dataset has been distributed in multi classes.

Support Vector Machine: The core idea of Support Vector Machine is to find a hyperplane that separates two sets of objects having different classes. It uses a technique called kernel trick to transform data and based on this transformation it finds an optimal boundary. It is considered one of the most robust and accurate algorithms among other classifiers.

Random Forest: Random Forest is an ensemble classifier; it takes multiple individual models and combined them into a more powerful aggregate model. So, let’s say we have different individual models, then there might be the case that they work efficiently because some part of the data set would be overfitted to the model. So by combining them, we can reduce the chances of error. Random forest built upon by aggregating n possible decision trees which might be generated by randomly picking data set row as root. So, as the dataset would be increasing, the possibilities of generating random decision trees would also increase and aggregating different decision tree models lead to an increase in the efficiency of the aggregated model, too.

REFERENCES:

Employee Work Appreciation based on Customers Feedback Project using IBM Cognitive Services

PURPOSE OF THE PROJECT

The purpose of the Employee Work Appreciation based on Customers Feedback project is to appreciate the employee’s work based on the feedback given by the customers and the employees. The feedback given by the customers to a respective employee is analyzed i.e. is it polite feedback/satisfied feedback…etc. Based on that, employees will be given appreciation.

Block Diagram:

Block Diagram

Flow Chart Diagram:

Flow Chart Diagram

HARDWARE/SOFTWARE SOLUTION

1. IBM Cloud
2. IBM Watson Tone Analyzer
3. Node-RED
4. Create an employee database in the IBM cloud and upload sample 4 employees feedback JSON files.

EXPERIMENTAL INVESTIGATION

1. Choose a Project Idea:

Employee Work Appreciation based on Customers Feedback.

2. Conduct Background Research
3. Compose a Hypothesis:
Based on our Study and the information gathered we can decide how well an employee is appreciable.
4. Design your Experiment:
First, we need to collect employee reports in which feedback is given by the customers.
Next, we give those reports as input to the Tone analyzer service which predicts the emotion behind the feedback.
5. Draw Conclusions:
After Building our model, we can able to know how well the employee is working and appreciate the employee’s work based on analysis of customer feedback.

Result Screenshots:

Sentiment Analysis:

Sentiment Analysis

Cloudant Dashboard
APPLICATIONS

This Employee Work Appreciation application is used for deciding whether the employee’s work is up to the mark or not.

This system can also be used for employees to check whether they receiving good or bad feedback from customers so that they will improve their work.

Node-RED Flow:

Node-RED Flow

IBM Cloud databases

Input employee reports stored in the employee database

IBM Cloud databases
Output sentiment by tone analyzer stored in sentiment database.

Development of Career Builder HTML & CSS Minor Project

  1. Introduction

There has been a demand for a career builder product, an application that can solve the problem of mock tests, and sample papers for different government and non-government projects.
The current trend of research on ed-Tech startups shows us that there is no specific application that solves this problem Several variants of this application are not focused on this. The current career builder web application project is to study and develop how this exam web and mobile application works so that we can build them in the forthcoming future.

  1. Motivation

Our country has too many government exams and the craze for it is too much but in the ed-tech market in this digital age, there is no stable application by which the aspirants can practice for the exams. In the modern era of 2021, the aspirants have to go to the local market and ask for the books for the preparation and mock exam of that particular government exam. Therefore we felt like there is a need for such a career builder application in the market. This is a pain point for many that we can see around us.

  1. Related work

Before starting this career builder project our team made many different google forms to know the need for this project and if something like this is required in the market or not.
Other than that we had previously observed people go to the local bookstore and ask for sample paper books and wait until it’s available also finding the papers is also tough since too many sites take extra permission and show nonrelevant ads.

  1. Objectives of the work

The objective of this career builder project is to make a well-focused web application (maybe a demo for this time and an upgraded version in the future and a mobile application too) so that the aspirants can find all the sample papers and mock exam papers in one place without suffering through the whole internet and make a business model in the future out of it.

  1. Technical Details

This career builder project is mainly developed using HTML, CSS, JavaScript, and JSON.
We are gonna develop an API to fetch data ( Questions and choices ) from the JSON file and are going to use external APIs for external data too. Some CSS frameworks will also be used for the beauty of the front end. The score of the user’s performance will be calculated and stored using local storage.

career builder Minor project ER Diagram

6. Hardware and Software Requirement Specifications

Write hardware and software requirement specifications.
The hardware required for the project is our team members’ laptops for programming and a WiFi router for remote work since we all are in different cities. Many software are used for communication and development as follows –

  1. Zoom – for planning and discussing the project and connecting virtually through video calls our team used the Zoom application which is also used in the tech industry for the same.
  1. Slack – for communication in the form of texts and images and also for data sharing except for the code we used slack and we could use other applications too but we choose it during a discussion because it is also used in the industry.
  1. Visual Studio Code – for the real work to be done in the programming we used the IDE called visual studio code. The two main reasons to choose this IDE only over the others are

a. We used it before in our college, therefore, we are comfortable with it.
b. It is widely used in the industry.

This software gave us support through its vast extensions some of which are

Live Server (main feature hot reload)
Prettier (format the code in ES6 the industry standard )

  1. Git Bash – for the use of the terminal for the Linux commands since 1 of our teammates uses Linux Operating System (Ubuntu) and it is beneficial to use these commands over windows commands (commands of Windows Power shell, etc ) since again because of industry standards – most of the startups in India provide mac book to their developers, the terminal of which also works on Linux commands and other companies also suggest to use Linux over windows at least for Command Line Interface.
  2. Git Hub – To deploy and share our code, it has many features like making branches and working separately together. To take the snapshot of that particular instant of the code for the future and other features like a staging area, commit, clone, and a remote code sharing system.
  1. Future Scope

The MVP version of the career builder minor project and its corresponding later versions can be used by the aspirants so that instead of finding papers on the whole web they can simply use a single website and study and practice without distractions.

  1. Conclusion

This career builder minor project is made with the idea of having a web application where the aspirants can practice with the sample papers of their particular exam.

Farm Assist – An Android Application for Farmers Assistance Project

Introduction:

Farm Assist (The farmers assistant project) is an android mobile application that is used to get the details about the crop price, and crop insurance details as insisted by the government. We can also get tips for skillful cultivation and get better yields. The farmer’s assistant application also provides the dealers to interact with the farmers so that they can enter the crop price details and buy the farmer’s crop.

Problem:

The main problem of the Farm Assist – Farmers Assistance project is that we are considering the loss of farmers due to the price of the crop that is sold to the dealers, the nonprofitable methods of cultivation, and the details regarding the crop loan issued by the government.

Technology stack :

1. Android studio.
2. CSS
3. Java
4. HTML
5. MYSQL
6. JSON
7. JavaScript
8. BootStrap.

The farmer’s assistant project mobile app consists of a basic entry for any user means anyone is allowed into the app without any login but the dealers are given a special button to register as a dealer.

In the crop section, the dealer information is stored in the database and shown when the farmer is searching for the best dealer the dealer’s list is displayed for him. the dealer is allowed to update the prizes when the updates are to be done.

In the Insurance section, the insurance of every crop is given and is updated in the database periodically when it is needed. In the agro-tips, the farmers are given the best tips for good crops and crop diseases.

App Home Screen of Farmers Assistance App

AGENDA:

  • Problems faced by farmers.
  • What are the solutions that others had given in the past?
  • Application demo.
  • Crop details.
  • Insurance.
  • Agro tips.

Problems faced by farmers:

  • The main problem that we are concerned is about the sale of crops to the dealers.
  • General market rates which are provided by Government are not implemented at the root level.
  • So to overcome this problem we are developing this application for the benefit of farmers and future generations.

What are the solutions that others had given in the past:

  • In the past govt. has started some committees in India to overcome this problem.
  • But it is not implemented all over the state due to the lack of knowledge of farmers and few inconveniences.

APP Demo:

The facilities which we are providing in our Farm Assist – farmer’s assistant app project

Crop details:

The first farmer will enter into the crops and then he moves into the district then the prices of the crop in that district will be shown in the farmer’s assistant android mobile app.

Insurance:

In this, the periodical update of the amount that the government has provided to the crop will be updated.

Agro tips:

  • Different suggestions like fertilizers, crop rotation, etc. are provided to the farmers.
  • The agricultural officers give these details regarding fertilizers, crops to be grown, etc.

Related Projects on Farmers & Agriculture based below:

Real-Time Assistance to Farmers and Health Sector Android App

Farmer’s Medium of Communication for Support Price of Crops

Farmers Buddy Java Project

Automatic Humidity Monitoring and Pumping System for Farmers

Design & Development of E – Agriculture Java project

Nearby Hotels Python Web Application

This is a simple web application that can be used to search hotels. This application will help in searching nearby hotels and also give weather reports of that place such that they can know the weather details priorly to near that hotel in order to travel. A currency converter is included with which everyone can view hotel prices in their desired currency. Additionally, discount coupons are included, which will help user to access the cheapest hotels nearby.

API’s to be used:

Google maps:

The google maps API fetches the data from google e.g. here Maps API is a server that returns information about a place, an establishment, a geographical location, or a prominent point of interest using an HTTP request. Methods are available for place search, details, and autocomplete queries.

The place API returns in JSON format.

Currency converter:

Planning to use online currency converter API web services. This API allows covering the currency to whatever the users needed.

This API returns data in XML format.

Weather API:

This API forecast the weather near the hotels, which uses information from the Rapid API: this API has all the information like temperature, humidity, wind, etc..

This API returns data in JSON format.

Discount coupon:

Planning develops discount coupon API, which gives what best hotels are available nearby with the best discounts possible.

This API returns data in XML format.

Technologies used:

  • JavaScript
  • HTML
  • CSS
  • Nodejs
  • Python