what differentiates m2m analytics

1Part of my Data Science TutorialsDr. Pradeep Mavuluri , Co-Founder, ATIS (www.analyticaltis.com)Dr. Pradeep Mavuluri , Co-Founder, ATIS (www.analyticaltis.com) Part of my Data Science Tutorials

M2M Data Science Course (Part of my Data Science Tutorials)

© Some 3rd party copyright material is reused in this tutorial under fair usage approach for educating purposes; hence, current presentation usage is restricted for educating purposes and fall under usual copyright usage terms.

2Part of my Data Science TutorialsDr. Pradeep Mavuluri , Co-Founder, ATIS (www.analyticaltis.com) 2Part of my Data Science TutorialsDr. Pradeep Mavuluri , Co-Founder, ATIS (www.analyticaltis.com)

What is M2M and How it is different from IoT? Machine to machine (M2M) is a broad label that can be used to describe any technology

that enables networked devices to exchange information and perform actions without the manual assistance of humans. – whatis.com

In simple words, M2M allows data exchange (communication) between machines, i.e. nothing but all about connecting and communicating with a machine (device, sensor, etc.)

e.g. A remote application enabling controls (while monitoring).

The Internet of Things (IoT) is a scenario in which objects, animals or people are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. IoT has evolved from the convergence of wireless technologies, micro-electromechanical systems (MEMS) and the Internet. – whatis.com

Again, in simple words, the potential interconnection of smart objects1 and the way we interact with all these objects is “IoT”.

Relationship: M2M → IoT (M2M is what provides the IoT), as smart objects/products are required to enable the internet of things.

1 Objects, that are generally built with M2M communication capableness's are often referred to as ‘Smart’. These objects/products pose such layer of artificial intelligence that enable all those possibilities to merge the physical world with digital (data) world.


What is M2M and How it is different from IoT ? (Graphical)

M2MCloud

M2M

Rem

ote

Devi

ces

Workbench

IoT

As, one can see from above M2M is an integral part of IoT, nevertheless, one should understand M2M as more of a vertical (involving all stages of a production or distribution) and as closed point of view. Further, IoT enables and provides a meaningful (or horizontal) approach wherein M2M devices are pulled together to address to provide solutions, whether they are for the industry, people or the environment.

Bridging ThisIsolated Here


Disaster & Damage Avoidance:• Assess and exploit data provided by different applications to predict a disaster or damage before it

happens. e.g. preventing hacks, aircraft/vehicle engine failure preventions, machine failure preventions. Risk Minimization in Business (more the information better the decisions):

• Deeper data mining allows a better decision-making than relying on pure strategic methods. Costs Optimization:

• Better prediction in hand reduces the costs. Increased Revenues:

• Retail’s or CPG’s can track and use the customer behavior in order to create dynamic and optimal layouts, marketing plans which will increase their revenues.

Better Healthcare, Energy Utilization, Farming (fertilizer & water distribution across the farm in the right proportions).

M2M Data Sciences – Why it is in demand? (Pros)

Leve

l of A

naly

tics A

dvan

cem

ent

Current Status Against Demand

Relatively Low

Very High Level(Unachievable due to rapid changes)

Moderate Level(Achievable with

right effort)


Can provide better customer service, business can charge by specific usage, effective advertising, and stability for your business as it opens the doors for precision monitoring of business activities and optimization of systems for real-time needs.

M2M Analytics – How they help business?

Monitoring of Business Activities

1) Receive events as streams and store to database

Purchases

Travel

Stream 1

Consumption

Stream 2

Stream 3

Stream 4

2) Can schedule pre-written scripts

Load Save

1. Data Cleaning2. Data Transformation3. Modeling4. Segmentation

3) Generate Results as streams

4) Can take help of visualization for better depictions

Stream A

Stream B


Initial setup for huge quantities of data itself is difficult, and also it is rapidly spreading to new markets. Complex process chain w.r.t. data coming from a potentially large number of communicating devices. It is more of long tail business needs then short ones and lagging standards as mentioned earlier.

M2M Analytics – How it differs from others?

More dependency on Machine Learning

Highly un-sizeable volumes

Decide what and how it

matters

Complex Data

Ingestion

Identifying Patterns


M2M Analytics – Future Look Like..contd. Advent of M2M devices, and physical interaction is leading to an astounding acceleration of data generation. This can be characterized by volume, velocity, variety, variability and complexity.

Time

Requ

irem

ent o

f New

Sc

ripts

“As notion of data driven strategies increasing, managers are emphasizing on “find some statistics to provide it”.

Let’s see how ‘User Behavior” prediction is getting changed due to M2M

Old Scripts

New Scripts

Earlier, when data was not astounding, industry was ok with existing analytical models, and used to run scripts that were thought to best (Old Scripts).

However, with the advent of M2M, constant checking and new analytics models are required (New Scripts)

what differentiates m2m analytics

Data & Analytics