Predict fires in the cities by using big data

The best-known examples of big data implementations is the analysis of customers' behaviour enabling to support the customer during a buying process very effectively.

So I was very happy to read about the usage of big data increasing the proactive measures in fight against the fire in the cities.

Based on certain factors like neighbourhood income, age of the building, electrical issues etc. authorities in New York City can identify the critical buildings with high probability of fire.

In the mean time the NY fire department has defined about 60 of these factors and based on them a ranking buildings database has been created in order of their risk of fire and which ones should be inspected first.
Before this big data analysis the NY firefighters inspected with high-priority buildings like schools and libraries more frequently. But all other inspections were random.

The new system makes it possible to reduce the number of fires and make fires less severe, according to the fire department.

Although one thing stays difficult...
How to evaluate the impact, the results and merits of the big data approach to prevent injuries or fire.

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Smart Data – Know thyselves!

The term “Big Data” we can find everywhere - in technical literature, different discussions and marketing prospects. But what does it really means for private user, public sector and companies?

Big Data remembers on the new technology for which the problems have to be found.




In the praxis we can see the active usage of the big data in marketing and sales. It is important to understand the historical data, but to extract the information influencing the decisions for the future is a little suspect.

The Big Data can help analyze an amount of data for which our human understanding is not sufficient enough.

What we need is not really the word BIG in the name but SMART. Smart data – is what I am working for. My team is working on the possibility to recognize and extract the usable information from a huge amount of data and data resources.

The problem of the Big Data is not a wrong technology or too primitive algorithms; there is a principal problem of the targeted goal - prediction. There is no sure method to predict the future!

For the decisions the people have to be the last instance to minimize wrong decisions or catastrophic outgoings. BUT… people are not rational… and it does not cause only wrong decisions. If Steve Jobs would trust blind the provided data then we wouldn’t have any iphone or ipad.

We need systems that support us, people, by calling attention on important coherences to be able to evaluate the considered perspective. But for this we do not need a Big Data but Smart Data.

So I can just say: ”Big Data – Know thyselves!”

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