This document discusses a solution for connecting smart homes in a smart city to improve fire response times. It proposes connecting temperature sensors in homes directly to the fire department so that alerts are sent immediately when a certain heat threshold is reached, eliminating delays from human response. This could improve response times by 83% and save up to 135 lives per year in Spain. A similar system called Smart Campo is described for monitoring agricultural conditions and preventing fires in forested areas.

1. SMART HOUSE in SMART CITY
Katerina Zalamova

2. Presentation
When you have Smart Houses in a Smart City, one see immediately
the natural communication between them. Here, we present an
example of this communication about the case of fire events.
Smart Houses
Smart City
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3. Problem Worth Solving
Not optimal use of the facilities potential: how long will it take for
the responsible person to call to the Fire House?
?
TIME
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4. Our Solution
Local intelligence optimized global smart infrastructure.
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We connect directly the alarm to the
Fire House eliminating the human
factor.
Fire

5. Our solution
The temperature sensor sends a alert message to the Fire House
when the sensor detect certain limit value. In the same time it
switches-on a signal alarm and it sends a message to the owner.
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6. The message:
it contains the option to
cancel the alert.
The data
The house plan
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7. Key Advantages
To be Smart but Efficient
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Response improvement of 83%
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Can save 135 human lives per year in Spain.
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No human dependance (prevent 65% of the cases of fire).
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Minimum cost saving of 384 Euros/year
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8. More examples...
SMART CAMPO
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It is the same application prepared to control the quality of the
agriculture production by controlling parameters as temperature,
humidity and sun radiation.

10. T1
- operative control
T2
- fire prevention
T3
- emergency call
Possible actions
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11. Key Advantages: Smart Campo
To be Smart and Efficient
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95% Response improvement against fire event
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98% Cost saving of damage
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95% Saving in operational costs, which represent 4M Euros for typical forest fire event
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12. The future
From Local To Global
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Big Data statistic studies from the local temperature data with prediction objectives
●
Prediction models on the local data for forest areas without sensors
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Global map created by local actions
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