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Détection intelligente des chutes et capteur d'alarme : Protection intégrale contre les chutes

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The fall detection alarm sensor is based on the following principles to realize fall detection:

Sensor Data Analysis

Built-in sensors such as an accelerometer and a gyroscope can monitor the human body’s motion state in real time.

When the human body is in normal activity, acceleration and angular velocity data fluctuate within a certain range.

When a fall occurs, the body acceleration will change greatly instantly, and the speed curve will also appear abnormal.

The sensor captures these data changes and transmits them to the system for analysis, so as to assist in judging whether a fall event has occurred.

For example, the acceleration of a person walking normally is relatively stable, but the acceleration will suddenly increase when falling.

Intelligent Algorithm Judgment

Using deep learning and other intelligent algorithms, the algorithm is trained with a large amount of sample data that includes various fall scenarios and daily activity scenes.

The algorithm learns characteristic patterns of falling actions, such as rapid body tilting and sudden drops in position.

In practical applications, sensors continuously collect data to input into the algorithm. The algorithm analyzes and judges the current human movement state based on the learned patterns. When it detects data patterns consistent with falling characteristics, it determines that a fall has occurred and triggers an alarm.

At the same time, the sensor can also combine the presence detection function to first determine whether there is a person in the area, and then further judge whether a fall has occurred, improving the specificity and accuracy of the detection

Help Center

Have a query? Please check this question and answers

Adopts 60GHz millimeter wave radar + AI algorithm dual verification mechanism:

  • When an abnormal posture is detected for the first time, the built-in speaker voice asks the user “Did you fall?”, and the APP alarm is triggered only after the user confirms “Yes”;
  • If the user does not respond or remains still for a long time (such as coma), the sensor will automatically push alarms to the family APP continuously and send text messages to emergency contacts simultaneously.

Based on the Doppler effect of 60GHz millimeter-wave radar, it detects human micro-movements (such as chest rise and fall during breathing, body movements caused by heartbeat) by transmitting and receiving radar waves.

There is no need to wear equipment or contact the skin. The monitoring distance can reach 2.5 meters (sleep state) and 1.5 meters (breathing/heartbeat accuracy monitoring).

Yes. Through dynamic/static presence detection algorithms, the difference between characteristic human movements (such as walking and waving) and pet activities can be accurately identified to avoid false alarms caused by pet activities.

The detection accuracy reaches the breathing level (it can sense human breathing in a static state).

By monitoring data such as the duration of falling asleep, total sleep time, number of times getting out of bed, breathing rate, heart rate variability (HRV), and combining it with AI algorithms to divide the stages of wakefulness, light sleep, and deep sleep, a sleep score report is generated to intuitively display key indicators such as the proportion of deep sleep and sleep efficiency.

No.

The transmission power of HOMERDA products is lower than the international safety standards (such as the FCC’s 60GHz radar maximum power density ≤1mW/cm²), and the radiation intensity is much lower than a mobile phone call.

It is non-ionizing radiation and is harmless to the human body if used for a long time.


Data is transmitted to the cloud via the AES-128 encryption protocol and stored on Amazon cloud servers/and other compliant servers;

All devices have no video cameras and only transmit abstract vital sign data (such as respiratory rate, fall alarms), without involving images or privacy images, eliminating the risk of leakage from the source.

Yes. Users can add multiple family members’ accounts through the APP and authorize remote viewing of real-time health data, sleep reports and alarm records, which is suitable for remote monitoring of children or multi-role collaboration in nursing homes.