MachinePulse at the Global Solar EPC Summit 2015 - 4th June 2015

•

1 like•722 views

MachinePulse

Unlocking Value of Solar Plant Data Through Analytics

CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10
CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20
CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30
CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40
CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50
CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60
CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70
CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80
CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90
CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100
CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10
CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20
CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30
CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40
CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50
CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60
CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70
CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80
CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90
CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100
CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10
CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20
CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30
CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40
CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50
CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60
CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70
CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80
CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90
CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100
CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10
CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20
CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30
CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40
CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50
CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60
CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70
CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80
CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90
CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100

MachinePulse at the Global Solar EPC Summit 2015 - 4th June 2015

More from MachinePulse

SolarPulse solves the problem of managing distributed solar sites

MachinePulse

SolarPulse helps PV plants reduce field expenses

MachinePulse

Effective response to adverse weather conditions using SolarPulse

MachinePulse

Assessing the impact of SolarPulse on performance of utility scale PV plants

MachinePulse

Value of solar remote monitoring and analytics for operational intelligence

MachinePulse

MachinePulseTM provides rapidly scalable, end-to-end solutions to enable a smarter industrial Internet of Things (IoT). Our product offerings are modular and domain independent. We offer a complete range of products from industrial grade data acquisition devices to a robust and scalable cloud platform, which can be deployed together or into existing IoT workflows with full flexibility. Using our products and rich domain expertise in the renewable energy sector, we have built applications to provide operational intelligence for the solar photovoltaic and wind energy industries. We are also working with our clients to deploy monitoring and analytics solutions for other industries. MachinePulseTM is part of the $16 B Mahindra Group and has an enthusiastic team of more than 60 data scientists, programmers, hardware and network specialists.

MachinePulse company presentation

MachinePulse

MachinePulse provides rapidly scalable, end-to-end solutions to enable a smarter industrial Internet-of-Things. Our product offerings are modular and domain-independent. We offer a complete range of products from Industrial grade data acquisition devices to a robust and scalable cloud platform that can be deployed together or into existing IoT workflows with full flexibility. Using our products and rich domain expertise in the renewable energy sector, we have built applications to provide operational intelligence for the solar photovoltaic and wind energy industries. We are also working with our clients to deploy monitoring and analytics solutions for other industries. Our philosophy is “Any Device, Any Network, Any Protocol”.

MachinePulse Products

MachinePulse

This presentation was given by Karthigai Muthu, Lead Big Data Analyst, at a meetup organized by the group Internet of Everything in March 2015. Through his presentation, Karthik provided a comprehensive understanding of available ecosystem tools and how they can be used to perform data engineering and data analytics. Karthik covers the following topics in his presentation: • Establishment of complete data pipeline using big data ecosystem tools. • Tackling of high velocity streams using various stream processing engines on cloud and performing Real Time analytics. • Tackling of historical data using big data ecosystem tools and migration of traditional infrastructure to big data environments. • Integration of big data ecosystem for data analysis using SAMOA , R and Mahout. • Deployments of big data environments on the cloud.

Managing your Assets with Big Data Tools

MachinePulse

This presentation was created by Ajay, Machine Learning Scientist at MachinePulse, to present at a Meetup on Jan. 30, 2015. These slides provide an overview of widely used machine learning algorithms. The slides conclude with examples of real world applications. Ajay Ramaseshan, is a Machine Learning Scientist at MachinePulse. He holds a Bachelors degree in Computer Science from NITK, Suratkhal and a Master in Machine Learning and Data Mining from Aalto University School of Science, Finland. He has extensive experience in the machine learning domain and has dealt with various real world problems.

Machine Learning and Real-World Applications

MachinePulse

These slides detail the IoT applications for industries and the challenges they face in implementing the related technologies. Two case studies are explored - the first one is about GE Aviation and the second one on analyses MachinePulse's solution for solar power projects. About the author Sachin is lead Business Development Manager at MachinePulse where he works on expanding new business opportunities for the company's solutions. Sachin has close to 10 years of experience in product design & engineering of complex embedded systems, technology consulting and business development. Sachin is also founder and manager of a Meetup group for IoT enthusiasts in Mumbai called IoT Mumbai (IoTMUM) http://bit.ly/1KIqNYT

Challenges & Applications in the Industrial Internet of Things (IoT)

MachinePulse

This presentation introduces big data and explains how to generate actionable insights using analytics techniques. The deck explains general steps involved in a typical analytics project and provides a brief overview of the most commonly used predictive analytics methods and their business applications. Vijay Adamapure is a Data Science Enthusiast with extensive experience in the field of data mining, predictive modeling and machine learning. He has worked on numerous analytics projects ranging from healthcare, business analytics, renewable energy to IoT. Vijay presented these slides during the Internet of Everything Meetup event 'Predictive Analytics - An Overview' that took place on Jan. 9, 2015 in Mumbai. To join the Meetup group, register here: http://bit.ly/1A7T0A1

Predictive Analytics - An Overview

MachinePulse

IoT Cloud architecture

MachinePulse

MachinePulse at the November Open Hardware Meetup, Mumbai 2014

MachinePulse

More from MachinePulse (13)

SolarPulse solves the problem of managing distributed solar sites

SolarPulse helps PV plants reduce field expenses

Effective response to adverse weather conditions using SolarPulse

Assessing the impact of SolarPulse on performance of utility scale PV plants

Value of solar remote monitoring and analytics for operational intelligence

MachinePulse company presentation

MachinePulse Products

Managing your Assets with Big Data Tools

Machine Learning and Real-World Applications

Challenges & Applications in the Industrial Internet of Things (IoT)

Predictive Analytics - An Overview

IoT Cloud architecture

MachinePulse at the November Open Hardware Meetup, Mumbai 2014

MachinePulse at the Global Solar EPC Summit 2015 - 4th June 2015

1. Presented By: Sachin Pukale, Lead Business Development Manager Unlocking Value of Solar Plant Data Through Analytics Presented in : 5th Global EPC Solar Summit 2015 Date: 4th June 2015

2. • • • • • • • •

6. • • • •

7. CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10 CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20 CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30 CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40 CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50 CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60 CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70 CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80 CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90 CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100 CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10 CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20 CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30 CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40 CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50 CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60 CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70 CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80 CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90 CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100 CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10 CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20 CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30 CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40 CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50 CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60 CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70 CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80 CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90 CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100 CB-01 CB-02 CB-03 CB-04 CB-05 CB-06 CB-07 CB-08 CB-09 CB-10 CB-11 CB-12 CB-13 CB-14 CB-15 CB-16 CB-17 CB-18 CB-19 CB-20 CB-21 CB-22 CB-23 CB-24 CB-25 CB-26 CB-27 CB-28 CB-29 CB-30 CB-31 CB-32 CB-33 CB-34 CB-35 CB-36 CB-37 CB-38 CB-39 CB-40 CB-41 CB-42 CB-43 CB-44 CB-45 CB-46 CB-47 CB-48 CB-49 CB-50 CB-51 CB-52 CB-53 CB-54 CB-55 CB-56 CB-57 CB-58 CB-59 CB-60 CB-61 CB-62 CB-63 CB-64 CB-65 CB-66 CB-67 CB-68 CB-69 CB-70 CB-71 CB-72 CB-73 CB-74 CB-75 CB-76 CB-77 CB-78 CB-79 CB-80 CB-81 CB-82 CB-83 CB-84 CB-85 CB-86 CB-87 CB-88 CB-89 CB-90 CB-91 CB-92 CB-93 CB-94 CB-95 CB-96 CB-97 CB-98 CB-99 CB-100

10.

11. • • • •

12. - By GTM Global PV Report, 2014

MachinePulse at the Global Solar EPC Summit 2015 - 4th June 2015

Recommended

Recommended

More Related Content

More from MachinePulse

More from MachinePulse (13)

MachinePulse at the Global Solar EPC Summit 2015 - 4th June 2015