Telling the future of energy with data

When Facebook shows you a list of friends you may know, Google letting you know an ETD to be on time for a meeting, and other e-commerce websites giving you recommendations on things to purchase, these are instances where machine learning is carried out on large volumes of data called Big Data.

According to Gartner, the big data market is worth over $250 billion and surely it is here to stay. Businesses of all sizes that deal with various applications have started to adopt these practices.

Companies are now focused on how to store and manage this voluminous data. How should we architect the business’ technology stack to gain value from Big Data in terms of HDFS, complex event processing, NoSQL and machine learning? Store data on prem or cloud?

By means of advanced analytics, and machine learning, companies tap into their insight-rich vein of experience and mine it to automatically discover and generate predictive models to take advantage of all the data they are capturing. Departing from the traditional style of looking into the past for insights, companies can now predict parameters that they want knowledge about.

The value of machine learning is in finding structures that we have never seen before and precisely modelling to assist in decision making.

At​ TTC, we are leveraging these to build intelligent models that can serve our customers recommendations about optimising their usage patterns and first hand information about dynamic pricing for compliant infrastructures. We are developing these models in the energy sector where machine learning is hyper critical

Weekend at IIMB Bootcamp

It is our please to let you all know that we will be at Indian Institute of Management, Bangalore (IIMB) for the Eximius Annual Bootcamp. We are one of the 20 startups selected to present there and have a booth for all two days. If you are around there please say hi to us and our team. We would love to hear from you all.

Data Is the New Dinosaur

Data is becoming one heck of a challenge to solve. Take a example of our Product ThingsHiFi- a 5KW Solar Grid-Tie UPS. This device send data every 30 seconds to ThingsCloud. On a daily basis we will have

(30/60)*60*24 = 2,880 insertions

Each data packet is around 6K byte, which makes

2880*6k= 17.2 mb/per day

For one month,

17.2 *30 = 516 mb/per device/per day

You can see where I’m going from here, even if we have a modest 1000 devices, then we will be looking around 500 gigs of data per month. Right now we are exploring different architectures to process this data.  Also, inserted  record has around 10 values.

So, per month per device it is

2880*10*30 = 864,000 values

Now, with 100 devices, it would be 86 million values, which needs to be queried. Suddenly from nowhere we need to work on big data …!!!

mThings Hardware

ThingsCloud is unveiling mThings hardware to prototype your products.  Below is the look and feel of the products. You can connect anything to this and control this from you mobile phone. Render_New_1

Product Features: Product TI CC3200 Chip, we will have both certified and non-certified modules.  This is a good starting point to connect your device to ThingsCloud Ecosystem.

Few more renders of the product Render_New_2

We are working out on the pricing and will soon update on this.

ThingsCloud Supports TI CC3200/CC3100 Platform

TheThingsCloud is a new Internet of things platform for connecting devices to cloud.  We provide REST Api and you can interact with your device like accessing a webpage.

To start with we support TI’s CC3200 Based systems and provide you easy integration to monitor you data streams.  Try out our new platform and let us know what you think.

TheThingsCloud Team