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Daviteq LPC Lidar People Counter
LoRaWAN
Sigfox
Sub-GHz
NB-IoT

Daviteq LPC Lidar People Counter

LPC

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1. Introduction

Daviteq Lidar People Counter is a sensor with static lidar sensor with advanced and ultra-low-power MCU to perform the counting algorithm.

To detect a person passing thru the gate, it uses lidar to measure the distance from the sensor to the object. As the changes in distance, it will understand a person passing thru the gate. Moreover, it can distinguish the direction of movement.

Precise counting with ultra-low-power to save energy is a big challenge with Lidar technology. Therefore, Daviteq engineers had a smart decision to put the PIR sensor so that the sensor can wake up to count when there is human reach the sensor, in the Field of view (FOV) of the PIR Sensor. When there is no moving human body in the FOV of the PIR sensor, the sensor will go to sleep mode for energy saving. When it detects the moving human body, it will wake up immediately to count people, the delay time of wake up is about 20ms.


When there is no moving human body, it will fall back to sleep mode within 20ms.


2. Principle of Operation

Counting people with this Lidar sensor consists of using the multiple zones of the sensor receiving area, and configuring it with two distinct fields of view (FoV), to alternatively get a ranging distance from them and consequently recognize the movements of a person. Using this method, the number of people occupying a meeting room, accessible from reasonably narrow access, is known at all times by detecting the entrances and exits of the attendees.



By measuring and analyzing the distances of targets within the FoVs of a front and back zone (see figure below), an algorithm can detect the direction a person crosses the area under the two FoVs. This algorithm "understands" that someone is under one of the FoV as long as the distance measured by the sensor under this FoV is between 0 and a threshold value specified in mm.

From a timing perspective, the sensor alternatively ranges on each of the two zones, for a very short period of milliseconds. It is possible to determine in which direction a person crosses the area, depending on in which order this person has been detected in the two zones, as shown in the figure below.



Dist_threshold mechanism

- The sensor will measure the distance from the sensor (on the ceiling) to the floor, when there is an obstacle, the person is under the sensor, the sensor will measure the distance from the sensor to the obstacle, and that person => will get the DistX  value

- When DistX < Dist_threshold, the sensor detects that someone is standing below

- When DistX > Dist_threshold + dist_hys, the sensor confirms that no one is under



Counting Hysteresis

The algorithm validates a crossing event only when a person has fully crossed the two zones. It does not validate the event when the person remains for a long time under the FoV or when the person decides to return from the place he came from, and hence the counting values are not changed.



3. Calibration

Commissioning the Lidar people counting sensor is an important step to getting the sensor working properly.


  • The Lidar FOV is 27° and the max distance is 3500mm, so please check the width and height dimensions of the gate so that the person must be within the FOV.


  • After that, checking the floor, the floor must be a flat and bright color. The very dark color (back or near-black color) floor can affect the distance measurement accuracy. In this case, using a light color carpet to gain accuracy.


  • The reliability of the algorithm relies on the accuracy of the setup which detects the distance between the sensor and the floor. This can be ensured only if nothing (e.g. no obstacle or static object) blocks the front and back FoVs. To assess if a setup is reliable, a significant number of distances can be measured with the sensor. Then, a histogram diagram can be established to confirm that the sensor is correctly set up and that no target is within its FoVs.


  • A threshold needs to be defined, which is achieved after having ranged the flooring material over a significant number of samples. In fact, the threshold should be chosen so that all the measured distances (when ranging the floor) are greater than this threshold. We recommend that at the installation of the application, the autocalibration routine is launched to calculate the threshold. This is because flooring material can be different in many locations.


Note: This calibration should be performed in the worst ambient light conditions, to maximize the jitter and obtain a threshold that is relevant to all possible ambient lighting conditions the counting setup is exposed to.


4. Application Notes

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5. Installation Notes

  • Do not install the sensor outdoors or indoors in areas with high intensity of sunlight.

  • Do not install the sensor in places where high dust particles or steam could affect the optical sensor.

  • Do not install the sensor near a door, as the door will blind the PIR sensor, preventing it from counting people.

  • Do not install the sensor in places where people are moving in parallel and nearby, as this will cause the sensor to wake up constantly but not count people. This problem will cause the batteries to drain quickly, in just a few days.

6. Troubleshooting



7. Maintenance

This Lidar people counter comprises 02 optical parts:

  • Lidar sensor with optical lense;

  • PIR sensor with lense;


These 02 parts need to be checked and cleaned periodically, depending on the environment. Use alcohol (70% volume) to clean the surface of the 2 above parts.


After cleaning, force the sensor to send data to check the distance values of the Front and Back zones to confirm the accuracy of distance measurement.


Do not use Acetone or other strong solvents to clean, it will destroy the surface of the sensor and cause malfunctions

8. Default Configuration