Different technological solutions are available to detect vehicles in parking lots. Magnetic sensors are the most common solution available, but there are other systems that combine more than one detection technology, such as infrared and radar, that are designed to offer greater reliability. This has sparked a debate on whether harnessing several technologies yields higher accuracy than using just one.
Single detection
IoT sensors are designed to identify vehicles. But they have to do more than just measure physical parameters; they also have to be able to interpret complex data in order to make accurate “decisions” about parking occupancy. For example, magnetic sensors detect changes in the magnetic field due to the presence of metal objects, like cars.
Magnetic sensors and other IoT devices have to be able to both measure these changes and identify whether or not what they are detecting is actually a vehicle to determine if the parking spot is actually occupied. Furthermore, they have to accommodate different weather conditions and possible interferences around them. If these factors are not taken into account when the technology is designed, changes in temperature and humidity could diminish the sensors’ accuracy. How to avoid this? By using advanced algorithms.
Multiple detection
Detection devices that use multiple technologies in their system, whether magnetic, infrared, or radar, stem from the idea of improving system reliability by overcoming the inherent limitations of each technology through the advantages of the others. Despite this, the combination of various detection methods has proven not to be as cost-effective as originally thought.
Contradictory results
One of the most common problems with multiple detection systems is conflicting readings. Let’s take the case of a system with infrared and magnetic sensors: the built-in infrared sensor might be dirty and incorrectly indicate that a parking spot is occupied, while the magnetic sensor in the same device may show that it is not. In such cases, the question arises as to which sensor is right. These discrepancies can send erroneous data that affect device accuracy and undermine confidence in the detection system.
Calibration complications
Well-calibrated devices are essential for them to function properly. Since each detection technology has its own requirements, combining them in a single device increases the complexity of the calibration process. A calibration error in one of the detection methods can affect the overall accuracy of the system and influence the configuration of the other technology used, requiring further adjustments and maintenance.
Energy consumption and investment
Multi-detection sensors typically require more power than single-detection sensors. This can lower the battery life of the device while increasing operational investment and maintenance costs. The initial investment also tends to be higher in these cases.
Case study: U-Spot Duo vs. U-Spot M2M
A few years ago, Urbiotica’s product portfolio was expanded with the addition of the U-Spot Duo device, which offered a multi-detection option. This sensor combined both magnetic and infrared detection to achieve greater efficiency, although ultimately its performance did not prove to be as effective as expected, especially compared to our U-Spot M2M sensor, which only uses magnetic detection.
The U-Spot M2M single detection device was 98% reliable in detecting vehicles in parking spots, meaning that it met and even exceeded the accuracy of the U-Spot Duo multiple detection system. The upshot was fewer incidents and consequently a better user experience.
Plus, the simplified design of the U-Spot M2M magnetic detection sensor means lower power consumption than infrared or radar sensors, which in turns leads to longer battery life and less frequent maintenance or replacement. Therefore, these sensors have been shown to be a more cost-effective alternative for vehicle detection in the long term.
Disturbance mitigation
One of the arguments in favor of using multi-detection technologies is often their ability to mitigate external disturbances, such as magnetic noise generated by power lines or railway tracks close to the parking spot. However, technological advances in magnetic detection sensors in recent years have made it possible to develop algorithms capable of filtering out such interference without the need for multi-detection systems.
U-Spot: Single-spot IoT detection
Today, magnetic detection sensors are often equipped with complex algorithms capable of eliminating constant magnetic noise and adjusting readings, taking into account the external disturbances. Other useful features include automatic calibration and easy adjustment of the sensor in real time without manual intervention or interceding with other calibration systems.
So, are multiple detection systems ultimately more or less reliable? The answer is that they do not necessarily guarantee better results. In practice, magnetic sensors to detect vehicles in parking spots, used on their own, have been proven to be 98% reliable. That is, they are an accurate, simple solution that avoids the potential complications associated with multiple technologies, from inconsistent results to the need for regular calibration.
However, the key issue is not defining the detection methods and determining whether one, two, or three is best. Instead, what matters is the system’s reliability and the way we can measure it. Therefore, projects should include clear specifications in their service level agreement (SLA) that guarantee the system’s reliability and stability.
At Urbiotica, we are experts in developing IoT technologies such as detection sensors to improve mobility in cities. We offer pre-tested, reliable devices that ensure optimal parking management.
