Because when it comes to home security, the smart use of data also offers countless advantages. But at what point do the paths of two so different worlds cross? That is, that of data management and of feeling safe at home.

The last word has to do with the arrival of the Internet of Things: it involves the integration of sensors, software and excellent network connectivity in the devices we use every day, which previously barely provided us with the least amount of information. , can now become a continuous data source used to improve home security.

Artificial Intelligence and Big Data in Home

Something that a few years ago was the perfect plot for science fiction movies has now become an increasingly present companion among us. And there are many technologies that, based on artificial intelligence (AI), directly impact the security of homes around the world. For example, imagine how a facial recognition system at your front door could give you the peace of mind that you know who is on the other side of the entry (even if you are hundreds of miles away).

And it is that, based on algorithms and different visual recognition techniques, Artificial Intelligence can identify different faces evaluating in real-time if there is a possible threat to home security. Thus, it could distinguish if the visitor is the usual delivery person assigned to our area and differentiate it from strangers with unknown intentions.

Science fiction?

Not much less. Likewise, a home security application based on Artificial Intelligence and Big Data could differentiate when movement inside and outside a property is abnormal, thereby detecting a strange presence.

On the other hand, another potential use of new technologies and Big Data for home security is its ability to memorize our habits -that is, record the way we behave inside our home in addition to adapting all systems such as light, television, music, temperature, door opening, etc., and adjust their behaviour to each particular situation that may occur. 

If we are travelling and we want to maintain the same activity in the lights of the house so as not to show our absence, these technologies will be most effective for configuring it in such a way.

Big Data applications for home security can also be focused on the protection of children. For example, sounding an alarm in case of detecting an unknown person near the child and sending the information in real-time to the police authorities to avoid a high-risk situation. 

All this is part of what is known as Smart Security and includes many applications based on new technologies and Big Data to make a home more secure. 

Do you spend long days away from home and want to check that everything is in order from your mobile? Or do you want to be able to communicate with a delivery person through an intelligent doorbell, so they can come back a few hours later? With the clever use of data for home security, all this is getting closer.

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Thus, over the next few years, Big Data will continue to be one of the critical pieces for the development and success of many companies since the collection of information will help many businesses to improve in aspects as disparate as sales, strategies or labour relations.

However, “the high volume of information will also force companies to use Smart Data tools that allow them to develop an intelligent use of the data obtained. 

Not all data provides the same value to companies. In this scenario, the quality of the information obtained will prevail over the quantity of stored data .”, they explain from Shapelets.

Smart Data is the necessary evolution of Big Data to treat data intelligently, as it allows companies to obtain, among others, the following benefits:

Added value

The volume of information that companies have is useless without a correct analysis. For this reason, Smart Data offers the extraction of added value to the data thanks to intelligent analysis. In this way, the strategies can be more precise and effective.

It is an opportunity for SMEs

Smart Data is not about quantity but the quality of information. For this reason, if small and medium-sized companies define well what information they need, they can take advantage of intelligent data analysis and not collect millions of bytes of information that will not be useful in their decision and improvement process.

Better customer or consumer service 

Smart Data allows defining precisely the information needed, making it easier for companies to find the most relevant information of each client or consumer, facilitating personalization with them, including life cycle management and interactions.

Prevent problems

The collection of raw data and the subsequent analysis of this information with Smart Data also facilitates access to information that helps detect failures and prevent them in advance by consulting what is decisive.

Know the competition better 

The intelligent analysis of the data allows companies to obtain information about the market, the sector in which they operate, and the competition situation, providing them with valuable tools to improve their position, such as price monitoring or change trends.

Smart Data is the added value Big Data needs to take advantage of its full potential. Without a correct and intelligent analysis of the data, companies will not obtain the competitive advantage that information collection offers them.

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The Internet has become the most well-known stage where billions of clients associate and offer data consistently. With such a lot of data surrounding us, Big Data is quickly becoming quite possibly the most specific domain across each industry.

What is Big Data

This alludes to the exceptionally huge arrangements of data that are yield by an assortment of programs. It can indicate an enormous variety of data, and the data sets are typically very huge to scrutinize or question on a regular computer.

Difficulties and techniques to analyze vast volumes of data and “big data,” an idea that exists since the Millennium’s start, aren’t new any longer. The techniques, for now, will whenever be considered traditional as well.

Big data gets created in multi-terabyte amounts. It changes quickly and comes in assortments of structures that are hard to oversee and handle utilizing RDBMS or other traditional innovations.

Big Data solutions give the tools, methodologies, and advancements utilized to catch, store, search, and analyze the data in seconds to discover connections and bits of knowledge for development and serious increase previously inaccessible.

Big Data Applications

Big Data applications help organizations settle on more enlightening business choices by dissecting huge volumes of data.

It could incorporate web worker logs, Internet clickstream data, web-based media content and movement reports, text from client messages, cell phone call subtleties, and machine data caught by various sensors.

Associations from various spaces put resources into Big Data applications to inspect enormous data sets to uncover every secret example, obscure connections, market patterns, client inclinations, and other valuable business data.

• Applications in Healthcare
• Applications in Government
• Applications in Manufacturing
• Applications in Media and Entertainment
• Applications in IoT

Big Data Uses

Like Facebook, Twitter, or Instagram, interpersonal organizations are an apparatus utilized by brands to study their shoppers and associate with them.

Organizations have additionally begun to assemble data from their shoppers. An organization work in big data and retail knowledge has introduced 15,000 sensors in the shopping spaces of 25 nations.

The data assembled with these sensors have identified that 36.8% of clients entering a shop in Spain have purchased something from the shop.

Advanced change organizations lead to the age of tremendous volumes of data that associations don’t have the foggiest idea of how to utilize and oversee.

What’s more, this is now being depicted in the work market. As per Randstad, a work administration organization, the big data expert profile is one of the three most famous profiles in 2017.

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