May 23, 2016

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Right Sensors for Object Tracking @ IoT-part 2

Continuing from last blog, we will now be exploring various criteria to chose the right sensor as well as classify sensors for obstacle detection solution.

Criteria to choose the right sensor

With so many choices available in the market from various vendors, it would be really helpful to know from where to start. A good starting point is to know certain features; some of which are listed below:

  • Type of Sensor – The presence of an object can be detected with proximity sensors and other sensor technologies like ultrasonic sensors, capacitive, photoelectric, inductive, or magnetic; or for advanced applications, generally image sensors and vision software like OpenCV are used.
  • Accuracy – The accuracy is a very important element, and it is useful to choose sensors with accuracy values between desired measurement margins.
  • Resolution – Depending on type of objects to be tracked, we can chooses sensors based on resolution. A high resolution can detect even the smallest changes in the position of the target.
  • Range – This involves choosing the sensors based on measurement limits.
  • Control Interface – To interface the sensor you have to know the types of the sensors. A wide range of sensors are 3-wire DC types, but there are many more types, including 2-wire DC or 2-wire AC/DC;
  • Environmental Condition – These include sensor operational limits like temperature and humidity.
  • Calibration – Calibrating the sensors is an essential step to ensure accurate measurement and efficiency.
  • Cost – Depends on a number of factors the sensor is supporting.

Sensor classification based on property

Proximity sensors – Several sensor technologies are used to build proximity sensors: ultrasonic sensors, capacitive, photoelectric, inductive, or magnetic;

  • Light sensor - It is a simple sensor that changes the voltage of Photovoltaic cells in concordance with the amount of light detected. A light sensor is used in very popular applications that track a line-marked path.
  • Color sensor - Different colors are reflected with different intensity. This simple sensor is in the same range with light sensor, but with a few extra features that can be useful for applications where the device has to detect the presence of an object with a certain color.
  • Touch sensor - The touch sensor can be included in the proximity sensors category and are designed to sense objects at a small distance with or without direct contact. This sensor is designed to detect the changes in the capacitance between the on-board electrodes and the object making the contact.
  • Ultrasonic sensor - These sensors are designed to generate high frequency sound waves and receive the echo reflected by the target. These sensors are used in a wide range of applications and are very useful when it is not important to detect colors, surface texture, or transparency.

Motion detectors – These sensors are based on infrared light, ultrasound, or microwave/radar technology.

  • Infrared sensor - An infrared sensor measures the IR light that is transmitted in the environment, to find objects by an IR LED. This type of sensor is very popular in navigation for object avoidance, distance measured, or line following applications.
  • Sonar sensor - The sonar sensor can be used primarily in navigation for object detection, even for small objects, and generally are used in projects with a big budget, because this type of sensor is very expensive.
  • Laser sensor - A laser light is very useful for tracking and detection a target located at a long distance. The distance between sensor and target is measured by calculating the speed of light and the time since light is emitted and until it is returned to the receiver.
    A laser sensor is very precise in measurement and in the same time is very expensive.

Image sensors – these are digital cameras, camera modules and other imaging devices based on CCD or CMOS technology.

Each IoT sensor type has its characteristics that can help making device better for a certain task or replaceable for other tasks. For example, an ultrasonic sensor works fine for solid objects but becomes lazy for soft or fuzzy objects. Also, some sensors are unable to figure the difference between a static object and a human being. All of these characteristics have to be clear before you choose the right sensor/sensors for your object detection solution.

So, with the help of comparative information on each type of sensor separately, you will now be able to find the appropriate sensor for any object tracking solution.

References