Bhadale Group of Companies - digital projects

Jan 2020
Digital Projects
Bhadale IT Pvt. Ltd | https://www.bhadaleit.com/

Our Projects Bhadale Group of Companies
Bhadale Group of Companies
Bhadale Group of Companies consists of Bhadale IT Developers Pvt. Ltd and Bhadale Real Estate Developers Pvt Ltd.
1. Bhadale IT Developers Pvt. Ltd is an IT and Computer Engineering company
This company provides consultation in areas of cutting edge technologies, research outsourcing, and software consultation related to data
center and related engineering practices
2. Bhadale Real Estate Developers Pvt. Ltd is a Real estate company
This company provides development of Infrastructure for IT Datacenter and allied sectors. It manages the engineering design, landscaping, civil
architecture, presently serving internal projects.
Bhadale Group of Companies has aggressive programs in place to serve the niche market.
Bhadale IT Developers Pvt. Ltd Programs and Services
IT Division programs
1 Cloud Architecture
2 AI , ML, Quantum technologies
3 Digital
4 Automation
5 R&D services
6 Engineering services
7 Mentoring Services
8 Data center services
9 Outsourcing
There are various services offered under each program, details are described below

Project details
Project brief Project details
Project name /
Location
Predicting Grant Applications, In-house project
Duration, Period,
Estimated Effort/
Estimated project
cost
Jul-Aug, 2018, 16 week project, $10,000
Services scope IT Discipline, Data Science services
Environment +
Details
Eclipse Oxygen, Scala Console, Apache Spark Notebook, sbt, Windows 7, Scala library, Java JRE, Spark’s Machine Learning library,
Databricks library, CSV dataset, Dataframe, Kaggle, and University of Melbourne Grants application
Demonstrated use of various functions available in Spark’s machine learning (ML) libraries to solve real world problems by Creating
Features, Building a Pipeline, Cross Validation and Model Tuning that helped to predict the outcome of grant application by various
scholars. Used Spark’s machine learning pipeline to fit models and search for optimal hyperparameters using a Spark cluster
o Basic setup of Spark Notebook and/ or Eclipse project
o Used Spark CSV package from databricks to load CSV data file
o Created features for given datasets by re-encode some data using withColumn on dataframe, adding new columns and
summarizing team data for successful /unsuccessful grant applications
o Convert features into Vectors for use in Spark’s estimators
o Setup a RandomForest Classifier using Spark’s ML library
o Build a pipeline to chain multiple Spark transformer’s to create a workflow
o Used the transformer to index and assemble for the output data frame
o Create a binary classification Evaluator
o Split the training and test dataset
o Fit the model and make predictions
o Tested to avoid overfitting by using cross validation when training the model
o Improved the model’s performance by using grid search to find better parameters

o Extract useful information from the results of the grid search, including:
 the average area under the ROC curve for each combination of parameters
 the parameters of the best model
 the feature importance of the best model
Dataset used: https://kaggle.com/c/unimelb , University of Melbourne
Screen shots /
Results
Grant status is the column that is the subject for prediction , other columns are features for the classifier
After Tuning using Grid search

Best model was a method on cross validation model
First and last two features are clearly the most important features for getting a grant
Project name /
Location
AWS Cloud ML, In-house project
Duration, Period,
Estimated Effort/
Estimated project
cost
June 2018, 6 week project, $8,000

Environment +
Details
o SageMaker, MXNet, Glue, Amazon Rekognition, Amazon Polly, Amazon Lex, Amazon ML, Spark ML, Kineses, and engines Tensorflow,
MXNet and Pytorch
Demonstrated the use of ML concepts, algorithms, training and predictions using AWS ML libraries, AWS EMR, Amazon ML and Spark ML.
Applied AWS AI stack to several use cases using, Amazon Rekognition ( Vision), Amazon Polly( Speech), Amazon Lex( Chat) use of
platforms like Amazon ML, Spark ML, Kineses, and engines Tensorflow, MXNet and Pytorch
 Setting up SageMaker IAM roles, buckets
 Setting up online Jupyter Notebook at AWS
 Configuring IAM, session for data retention at S3 for notebook
 Python Code to import, configure modules and setup scripts for run
 Setting up of data models, data pipelines, and data transforming stages
 Python Coding for interfacing, using and getting results from various AWS modules
 Splitting dataset into training and production based on ratio
 Training ML models, using various models Linear, Regression, and applying AWS features
 Rerunning the trained model with sample test cases to find the performance
 Fine tuning the hyper parameters and using functions for aggregating, normalizing data for charting
 Plotting of results in chart, scatter, bar diagrams
Screen shots /
Results
Project name /
Location
Akka project, In-house project
Duration, Period,
Estimated Effort/
Estimated project
cost
May 2018, 6 week project, $4,000

Environment +
Details
o Eclipse Oxygen, Akka library, Scala library, Play webserver, and Typesafe Activator
This project demonstrated the need for proper planning, setup, configuration and running of Akka project based on standard templates.
This demo showcased our client about the design, architecture, and deployment models to the cloud, especially JVM based AWS cloud
o Installation of required Typesafe activator files,
o Configuration of environment vars., starting of Play http server,
o Command line operations in shell like new scala file,
o Activator UI, Activator RUN, Activator Eclipse ( to make eclipse proj files),
o Importing project in eclipse, & Akka plug-in in eclipse.
o Design of classes based on Akka Actor library
o Testing of Actor responses from IDE, and Scala console
Screen shots /
Results
Install Typesafe Activator ver. 1.3.5 or latest ver, 1.3.12
Create new akka project using cmd from activator folder

Activator new Myakka hello-akka
After project is created run the same using run cmd from the project root
I ran cmd : activator ui; below server started
Once server started, using browser, visit this link
http://127.0.0.1:8888/home or http://localhost:8888/home and get below page

You can either use UI or cmd to build the sample. From project root type: activator run
Project loads sbt and builds. Output shown below

You can also use activator eclipse or play eclipse to create eclipse files for IDE import. You can then use IDE to edit, debug files
Use help cmd if you wish to know more and see the installed templates for akka, scala, and other samples that you can use to create new
projects
Project name /
Location
Scala projects in Eclipse using Play web framework, In-house project
Duration, Period,
Estimated Effort/
Estimated project
cost
Apr 2018, 5 week project, $4,000
Environment +
Details
o Eclipse Oxygen, Akka plugin for Eclipse, Akka Actor library, Scala, JDK, Play web server, play framework templates, Typesafe and
Activator
This project was to demonstrate the setup of Scala, Play framework in Eclipse environment and showcase the use of Scala language
features and create a simple play framework based webpage

Tasks involved Installing Play, Eclipse, Scala and JDK, using shell commands like Play NEW (create Scala proj) Play RUN( start Play http
server), Eclipse ( create Eclipse files). Import files to eclipse, run the application and verify the webpage at localhost.
o Installation of required Typesafe activator files,
o Configuration of environment vars., starting of Play http server,
o Command line operations in shell like new play project using scala
o Importing project in eclipse, & Akka plug-in in eclipse.
o Design of classes based on scala
Testing of responses from IDE, and Scala console
Screen shots /
Results
Install Play, Eclipse, Scala and JDK. Set the JAVA_HOME, PLAY_HOME and SCALA_HOME. Also add the respective bin folder path to the
PATH variable
Create new play project “hello” as shown below. After that go to the root folder of hello and type command “play run” and see that the
server is launched
Quit the server and go to the root of the help project. Enter the PLAY prompt by typing play, once in play prompt, type “Eclipse”. This will

create the Eclipse project files.
After this Go to Eclipse, Import the eclipse files using Import->General files.
Go to Play folder to hello root, start the server using PLAY run. See the following at http://localhost:9000

In Eclipse, modify the VIEW folder, index.scala.html to your desired message
This View will trigger to show the content from the controller: Your new Application is ready”
Go to the : http://localhost:9000/ and refresh. This will show

Project name /
Location
Big Data Analysis for Airline Delays, In-house project
Duration, Period,
Estimated Effort/
Estimated project
cost
Dec 2017, 8 week project, $10,000
Environment +
Details
o Revolution R, FAA Data set, Microsoft HPC, Microsoft Azure Burst
o FAA Data set from : http://stat-computing.org/dataexpo/2009/the-data.html
o https://docs.microsoft.com/en-us/machine-learning-server/r/tutorial-revoscaler-large-data-airline
Using ML R libraries for analyzing FAA Dataset 2007
Project using R for Data Analysis and mini-chart plots using R libraries.
Develop Model using rxLinModel, use of R functions like rxSummary, rxQuantile, rxCrossTabs, rxCube to analyze Aircraft delays and the
relationships w.r.t the weekdays, holidays and any deviations from standard schedules. Use of transformations for dataframe to XDF
format and use of Transforms/ TransformFunc for data manipulation and display using Histogram to verify the changes
 Setting up the local and cluster environment –Microsoft HPC, Microsoft Azure Burst, LSF
 Define Compute context using RevoScaleR ComputeContext for defining hardware, monitoring, and failover
 Import Dataset and scale down for a small subset
 Summarise variables like 7 days of week category
 Use Linear model to predict arrival delay
 Summarise the model and see its performance
 Use advanced features like rxLinMod, rxPredict
 Predict using advanced features and see the improvements
 Train model , cross-validate model and retest the model
 Observe the model performance and see the delay predictions are accurate
Screen shots /
Results

Adopted from AWS
Summarise variables Examine a Distribution of Departure Time

Examine a Distribution of Arrival Delay Predict Arrival Delay by Day of Week
Summarize model and see the std. errors

Project name /
Location
AI project- MAS methodology selection tool for Efficient Multi-Agent System, EU Client
Duration, Period,
Estimated Effort/
Estimated project
cost
Mar 2017 – May 2017, 5 months project, $10,000
Services scope IT Discipline, AI services , Mentoring services
Environment +
Details
o Multi-Agent system methodologies, Thesis project, Java, AWS, Spark , Agent-oriented software engineering (AOSE), O-MaSE
methodology, GAIA methodology, INGENIAS, MAS-CommonKADS, Methodology for BDI agents
I offered mentoring services to Mr. Himanshu in his MS research work in a European University. I offered him the clarity, and basics of AI
and MAS concepts, applicability of the methodologies like AUML, Prometheus Tropos, O-MaSE and GAIA methodology. I also guided him
about using MAS in a cloud platform and use of Big data and AWS ML cloud platform for his project.
Mini-project for MAS methodology selection using several criteria and use of an expert system to select right tool based on the research
work. MAS methodology selection tool - Expert system, Industry framework for features, AI /fuzzy logic used and use of statistics, Java
based tool hosted in AWS use of Spark to leverage scalability
 Planning for thesis content, themes and template
 Offering expert review comments for researching the literature for methodologies
 Setting up project environment, tools, and platforms
 Offering advice on preparation of the Research Summary and presentation
 Offering review for the final thesis submission
 Providing insights of the AI / ML concepts, use cases, project samples and case studies
 Offering hands-on experience to enable easier learning
 Providing Anti-plagiarism tools, review and supervision

Screen shots /
Results
Elements and interactions in MAS(adopted from Alonso,et al, 2007) Genealogy of methodologies(adopted from Sudeikat, et al, 2005)
Generation of IDK model (adopted from Pavon, et al 2006) TAOM4e and eCAT( adopted from Moramdini, et.al. 2007)

MAS system for airport ( adopted from Sanchez-Pi, et al 2010)
Project name /
Location
Microsoft infosec for cloud and mobile, Client project
Duration, Period,
Estimated Effort/
Estimated project
cost
Mar 2016, 2 week project, $2,000
Services scope IT Discipline, Cloud services
Environment + o Microsoft STRIDE, Live ID, Azure AppFabric Access Control, WIF, AD Federation Services 2.0, STS, FP tokens, Azure gatekeeper design

Details pattern, Security Development lifecycle(SDL)
Demonstrated to client the basics of cloud security, security assessment plans, compliance checks, vulnerability testing, use of Azure
based Information security offerings, controls, measures and development lifecycles, and mobile-first, cloud-first world. Also
demonstrated the industrial standards like ISO 27001, PCI-DSS and others from NIST, and SANS
My presentation demonstrated a first level view of Microsoft's state-of-art technology Info-Sec offerings.
This presented the cloud security methodology being adapted to newer requirements of SSO, Active Directory integration ( Cloud and on-
premise), Identity providers ( Google, Skype, facebook), various combinations of logins for use cases that host AD in several locations, use
of design patterns like gateway, redundancy of DMZ/ hardware security by use of service bus
 Setting up of sample Azure website for demonstration
 Providing cloud based login, and demonstrating the access control measures
 Showing the working of federation, token passing and SSO authentication
 Adding entities to AD and showcasing the control measures, and effective policies
 Offering mobile based security features of Microsoft Azure
Screen shots /
Results
Adopted from Microsoft

Project name /
Location
AI project - Ambient multi-agent system, Client project
Duration, Period,
Estimated Effort/
Estimated project
cost
Nov 2014 – Mar 2015, 5 months project, $25,000
Environment +
Details
o IoT, Mobile App, Bigdata, Ambient Intelligence, RFID, Location aware services, monitoring, health condition and patient
requirements, hardware and software modules, interfaces, wireless router, wireless protocols like Zigbee, ambient sensors ,
Healthcare, and Security
In this project, I guided a MS student in his master’s research work in Tunisia; this is a society of mobile AI agents, Zigbee, and IoT sensors
that sense the ambient and take appropriate actions.
I mentored in the design of healthcare solutions using IoT, RFID, for hosting the project in location aware webserver. Migration of agent
to different server based on patient being shifting from OT to special / general ward and offering key information about the history for
attending nurses to view remote data and attend to the patient at specified time and specific drug or diagnosis.
 Problem definition, project scoping, and project roadmap
 Planning of project elements, devices, network, configuration, and protocols
 Setting up project environment
 Design of GUI pages, interfaces for mobile and Zigbee device
 Networking of devices and data capture
 Data storage and retrieval operations and analysis of same
 Tabulation of Results for the pre and post implementation and improvement factors

Screen shots /
Results
Architecture of SpatialAgent framework ( adopted from Ichiro Satoh, Japan) ZigBee device used in MAS( adopted from Dante,et.al
Spain)
RFID technology in MAS wrist bands and a USB Desktop reader( adopted from Dante,et.al Spain) Positions of RF tags in floor and map
viewer agent view(adopted from Ichiro Satoh, Japan)

Project name /
Location
Cloud business strategy- for retail shoe company, Client project
Duration, Period,
Estimated Effort/
Estimated project
cost
Aug 2014 – Sep 2014, 8 week project, $6,000
Services scope IT Discipline, Cloud services
Environment +
Details
o Azure, Migration Wizards, Aspx pages, HTML5, MS Sql Server, 3 tier setup and configuration in cloud, Digital certificates, domain
setup
Generated strategy document for modernizing the website and hosting it to cloud. Analyzed and developed the overall enterprise
solution for retail operator in Toronto, ON. Assisted in concept design deployment / migration of legacy to cloud platform.
This helped the business owner to leverage on the cloud platform and move his few static web pages to cloud and enabled him to scale
and have a hi-availability for better customer satisfaction.
 Planning the strategy for cloud migration
 Setting up the cloud demo environment for the migration
 Running the migration wizard for the sample website
 Showcasing the security features and hacker proof to ensure better business
Showcasing the availability, admin dashboard for resource management and website configurations

Screen shots /
Results
Project name /
Location
Smart metering solution, Client project
Duration, Period,
Estimated Effort/
Estimated project
cost
Jul 2014 – Aug 2014,6 week project, $3,000
Services scope IT Discipline, IT + Engineering services
Environment +
Details
o SAP Utilities, Azure IoT, Smart grid, Smart meter,
Designed proof of concept and idea, presented the hi-level concepts, technology of smart meters to a Director in UAE.
I showcased how SAP metering solution can be integrated with smart grid. Showcased how the SAP interfaces for metering and bills in
real-time for effective utilization of energy. Integrated solutions based on SAP + Azure, IoT, use cases, h/w, s/w integration

Screen shots /
Results
Adopted from SAP

Project name /
Location
Accelerated MS course training, Client project
Duration, Period,
Estimated Effort/
Estimated project
cost
Mar 2013 – Mar 2014, 1 year project, $12,000
Services scope IT Discipline, Mentoring services
Environment +
Details
o Java, Python, C , Data Structures, Android mobile App, projects, weekly assignments, exam preparation
Arif Plaza Inn: The website had to be competitive and this needed use of AI for understanding customer interactions, booking patterns
and based on the dataset collected.
Design of website using PHP, LAMP stack. Design of ML code using Python. Use of ML algorithms to classify, normalize, display and
provide customers a better user experience by presenting to them features/ services /menus as per the recommended results of these
algorithms; leveraged NoSQL for storing of unstructured data, retrieval and display, ML algorithms for design of recommender engine
and predicting the outcomes. Use of Python recommender based on bookings data – Python libraries like panda, JavaScript lib. used to
design and develop the front and back end
HangMan / Golf game: Reviewed the design , coding of GUI interfaces, classes, logic, Java classes and testing of the game
Algorithms: Review of base code, applied proper logic for better readability, comments, performance and run times charting
 Setting up project environments for Windows, Linux, Java, Python and Android mobile
 Mentoring for the design and development of project class files, coding, data structures and templates
 Providing trouble shooting of algorithm codes, running time and verification of results
 Design of mobile app
 Assist in weekly assignment submission for 10 advanced courses
 Provide advice, guidance for the project work, project documentation and submissions
 Remote web site admin tasks for various applications, projects and web pages

Screen shots /
Results

Binary SearchTree operations BFS and DFS for a maze operation
Hangman game in Java Golfers game in Java and Par Score

Project name /
Location
Solution for IBSYS Telco fraud , Client project
Duration, Period,
Estimated Effort/
Estimated project
cost
Oct 2012 – Mar 2013, 6 month project, $6,000
Services scope IT Discipline, Cloud services , Engineering services
Environment +
Details
o Azure, Azure security functions, Private cloud, auditing of financial loss, migration to Azure SQL Server
Conducted technical analysis, inspection and auditing of financial irregularities in IBSYS, Canada. Preparation of the initial investigation
case report for future investigation by Govt. officials.
Demonstrated use of key tools from Azure platform and recommended to migrate workloads to Azure private cloud and use of cloud
security for quality standards that help reduce the risk associated with network swapping, cross-site injections, malware and routing of
legal Telco traffic through pirate servers
 Studying the existing datacenter layouts and finding the honey traps
 Reporting the hacking activities using spyware, virtual network that was not noticed
 Estimating the revenue loss that was about $1million year
 Preparing reporting documents for legal actions and claims
 Engineering techniques for testing of servers, network routers and performances
 Offering Azure based private/ public / hybrid workloads for voice and non-voice traffic
 Offering feature-benefits for migrating to cloud
 Anti-hacking techniques, strong tenant isolation and security features of Microsoft Data center

Screen shots /
Results
Project name /
Location
MS - Deriving project-values of multi-agent system, project work
Duration, Period,
Estimated Effort/
Estimated project
cost
Jun 2011 – Dec 2011, 6 month project, $6,000
Services scope IT Discipline, AI services
Environment +
Details
o Java, JADE, Agent development, MySql, matplotlib, Use cases, Thesis writing, Telecom, Disaster management, B2B marketing
This project used Java based AI algorithms and AI agents for collection of raw data from a site from an instrumented and digital feeds like
RSS, Atom, converted that to normalized format, stored in a MySql db for feeding to the big data modules for further analysis and
generation of plots.
Leveraged the supervised/unsupervised learning techniques, AI algorithms for data mining, classification and regression to develop a
prototype model of the multi agent system that led to proper resource allocation, decision making for Telco and disaster management
systems, use of IoT sensors at disaster locations.
 Designing the hypothesis of the project

 Setting up of the environment for Java, JADE, MAS agent design, develop and test
 Generating code for various MAS agent tools and comparing them for their agent attributes
 Tabulating the features of each tools and reporting them for support of hypothesis
 Deriving conclusions for the project benefits added to showcase for team benefit
Screen shots /
Results
Agent Definition Code generation using IDK

Disclaimer: This document is for educational purpose and illustration of work samples with estimates only. No intention for any copyright infringements.
For further details, please contact:
Bhadale IT Pvt. Ltd
Program Manager: Vijayananda Mohire, +91-9741040195; Email: vijaymohire@gmail.com

Bhadale Group of Companies - digital projects

Bhadale Group of Companies - digital projects

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