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You can talk with professionals and figure out how AI and IoT Technology of Triplet can be applied to your business. Leave us your contact info and unsolved issue that cannot be dealt with current methods, then our AI and IoT professionals will get in touch with answers.

Disaster/Environment monitoring

From precise detection to timely response within the golden time

Early response, more than being prepared

To prevent false alarm, traditional fire detectors only issue alarms when fire has somewhat proceeded, so that it only can help evacuating people. Fire detectors by Triplet let extinguishing activities start within golden time by its state-of-the-art technology which precisely detects fire ignition and quickly notifies 911, so that not only human life but also precious assets can be saved.

No more false alert

By comprehensive fire and disaster detection through combination of various sensors and AI camera technology, precision of alert has been improved. Triplet will help you not to be exposed to danger caused by turned-off alarms due to frequent false alarms, or prevent unnecessary firefighter dispatches.

Precise fire data

Fire video and precise inside location information captured by AI camera will be provided to the fire department, so that they can quickly understand the scene and improve success rate of fire suppression.

High-quality service
at economical pricing

HIGH-QUALITY SERVICEAT ECONOMICAL PRICING

With LTE network, realtime video, high resolution image, voice data can be transmitted 50 times faster than traditional LoRa network and 10 times faster than NB-IoT. Also, the terminal itself is built based on edge computing which can process data, so the processing time is faster than the cloud computing, and the solution is built with economic pricing and superb security.

Prevention of facility collapse and surroundings monitoring

The hardware can measure the change of slope where it is located, preventing risk of collapse due to natural disasters such as earthquake and deterioration of the facility.
In normal time, the hardware monitors factors determining space surroundings such as temperature, humidity, and air pollution, in real time, and maintains optimal conditions.

Maximizing prediction of disasters

Traditional solution had to change settings of the program according to the monitoring environment and condition, lacking versatility.
However, AI solution which keeps learning, can be easily applied to new environment and conditions. AI predicts spaces exposed to disasters by deep learning of sensor data and external surroundings information, and alerts the occupants the disaster occurrence risk in advance to prevent the disaster.

Recommended for any spaces where disaster/surroundings monitoring is required.

Recommended for these space

Factory and warehouse

Preventing property damage and maintaining right temperature and humidity for products

Traditional Market

Providing life safety net to citizens and small business owners

School and hospital

Providing safety net for fire-vulnerable and surroundings-change-vulnerable places

Big commercial building and high-rise

Reducing necessary cost and man-hour for safety inspection

Residential home and accommodation

Managing safety and air quality smartly

Time-worn building

Applying high-tech safety service with economic cost

Factory and warehouse

Preventing property damage and maintaining right temperature and humidity for products

Traditional Market

Providing life safety net to citizens and small business owners

School and hospital

Providing safety net for fire-vulnerable and surroundings-change-vulnerable places

Big commercial building and high-rise

Reducing necessary cost and man-hour for safety inspection

Residential home and accommodation

Managing safety and air quality smartly

Time-worn building

Applying high-tech safety service with economic cost

Contact Us

Find out how Triplet, AI+IoT professionals, can bring amazing insight to your business now.

Contact Us

M help@triplllet.com

P +82 70. 4354. 8894
F +82 2. 6919. 1357
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