Defining selection criteria
Whether you are an enterprise facilities manager, municipal transportation department head or a private parking asset operator, selecting among various available smart parking solutions is not as easy as it may appear at first glance. Each of those solution approaches have different pro’s and con’s and each of them make work better than another for your specific project’s needs, requirements and budget limitations.
While not claiming to be exhaustive, this post, together with an earlier post by our CTO Yury Birchenko, targets to offer some structure around these various alternatives to help you decide which solution would work best for you. Here at Nwave we strongly believe that it is the informed buyers that make the best decisions personally and for the company they work for. This overview, combined with our post on sensor KPI’s, should also help you decide if the features of Nwave’s smart parking solution may or may not fit with your project needs.
To set the stage, let’s discuss what are the main requirements for making a “simple” parking solution to be a “smart” parking solution. As discussed in many of our previous posts, the core basic objective of a smart parking solution is to identify a vehicle’s presence or absence in a particular area or a particular parking space (for per-space solutions) with a high degree of accuracy, and to pass on this data into various apps for visualization and analysis – to be available for drivers and for parking asset managers and enforcement officers.
The next-level objective is to identify not only a “yes”/”no” on a vehicle’s presence, but to be able to identify exactly which vehicle it is (and then who it belongs to) and/or who is the driver who parked in a particular area or parking bay to enable e.g. special user management (such as handicapped, EV, delivery vehicles) or parking payment solutions. These latter capabilities is what we call “advanced” functionality for smart parking solutions.
Keeping in mind the objectives of smart parking solutions above, we find that the two most important considerations for comparing alternative smart parking solutions are:
- Accuracy of solution (accuracy of detecting a vehicle presence/absence)
- Total cost of solution (consisting of the initial purchase and installation cost as well as future maintenance cost, e.g. battery replacement)
Additional criteria typically would include:
- Privacy concerns (e.g. for camera-based solution)
- Visual appeal (amount and visual perception of solution’s hardware)
- Need for advanced capabilities (e.g. need to identify a particular car or driver)
Comparing the alternative solutions
Below is a four-quadrant chart that helps to visualize the four main types of solutions available today on the market, using Total Cost and Detection Accuracy as the two axis. These four types of alternative solutions are:
- Mobile Apps
- Cameras/LPR
- Ultrasonic Radar/Lidar
- Ground Sensors (and Nwave sensors in particular)
Let’s take a look at pro’s and con’s of each of these main alternatives in a little more detail.
Mobile Apps
Mobile Apps is the smart parking solution that is already widely in the US and around the world to pay for on-street parking. In the US, such solution would be represented by mobile parking apps such as PayByPhone or ParkMobile. Vehicle positioning in this solution is based on the GPS signal received by the user’s smart phone. By the nature of the GPS signal, these solutions can only provide an approximate location of the user. This is why when using these apps, the user needs to confirm on his or her phone the parking zone number the car is parked in to initiate a paid parking session.
Thus, though being low-cost (no hardware needed other than a phone and an app), this solution clearly lacks accuracy. From the user-experience point of view, the availability of parking spaces can only be shown in relative terms for each zone, a particular available spot cannot be identified. Additionally, the user needs to manually enter and confirm the zone to initiate a parking session and then manually extend the parking session to avoid violations.
From the parking operator’s and enforcement agency’s point of view, they can only see occupancy availability and violations on per-zone basis and, essentially, based on voluntary users’ actions to confirm his or her location via the app when initiating a paid parking session. Identifying specific car parking violations, such as non-payments or overstays, still need to be handled by inspection officers making the rounds across parking areas.
Clearly, from both the user’s and parking operator’s point of view, it would have been a great advantage to see real time data for each individual parking bay and to be able to initiate payment transactions via automatic linking the car/driver to a particular parking space, without a need to re-confirm the zone number
This is what the other solutions we discuss below are targeting to do – to provide per-space occupancy data as the base solution, and specific vehicle and driver as the advanced smart parking solution.
Cameras/LPR
This solution is using video cameras located on posts or garage structures (can be either specialized or security cameras) to identify vehicles location and License Plate Recognition (LPR) technology to identify and read the license plate number. This solution definitely has it’s advantages, especially if you need to monitor large and open spaces. To demonstrate the advantage of the camera-based solution, you would only need one camera with LPR at the entrance and the exit of a garage to identify whether a particular car has entered or left the garage based on it’s license plate. However, if you want to know which particular floor the car has parked on, and then in which particular parking space – the number of cameras needed to provide accurate solution grows exponentially, and so does the cost of such solution.
Additional considerations that can work against a camera-based solution could be:
- Requirements for wires, conduits – potentially creating a cluttered look in a garage situation
- Incidental lack of accuracy due to the line of sight from a camera to a car’s license plate being obstructed by a tree branch, large vehicle or image recognition by LPR algorithms impacted by bad lighting or light reflections from the license plate. Taken these factors altogether, modern per-space camera-based solutions can typically still provide a high-80s – low 90s % of detection accuracy at best, compared to 95%+ accuracy for ultrasonic/radar and ground sensor solutions.
- Long time required for vehicle identification. Despite modern computing capabilities, it can still take up to 2 min for some camera-based solutions to process the video footage and apply LPR algorithms to identify an occupancy event, vs. seconds for ultrasonic/radar and ground sensors solutions.
- Privacy concerns. Cameras record everything they see, including people’s faces, and typically pass on this data to Cloud for LPR algorithms to be run. Though some solution claim to be able to process the image data locally and/or erase the human face images right at the capture time, one cannot be exactly sure what happens with all of the sensitive information being recorded – at least from a driver’s point of view who may not be familiar with all of the security features put behind the solution.
Ultrasonic Radar/Lidars
These solutions use sensors mounted on light poles or garage structures that use various types of radars or lidars to identify vehicle presence.
These solution share a lot in common with camera-based solutions in terms of limitations on line of sight and requirements for significant hardware infrastructure to install and service these sensors.
If installed over each parking bay, this solution can be quite accurate, but can be quite expensive due to the cost of the supporting infrastructure. They also lack (at least by themselves w/o side solutions) the advanced functionality of identifying a specific car and driver that some of the other solutions can do.
One place where you might have seen such solutions is in underground shopping mall parking areas – green and red lights over each of the parking bays indicating space availability. While this green/red lighting is helpful for drivers to find an available parking spot, in addition to the considerations already mentioned above, different customers may have different views about the appeal of this quite busy “Christmas Tree” look – but, of course, it’s is matter of a personal taste.
Ground sensors
Ground sensors are typically placed on or in the ground at each of the parking bays and transmit occupancy information from each bay to gateway/base station in real time using a wireless transmission protocol. These sensors are also typically battery-powered, thus providing for a completely autonomous operation and no need for conduits, wires, electricity etc. – resulting in significant cost savings on this supporting infrastructure and also providing a clean and minimalistic look for the solution with only compact sensors on the ground. Base stations, in turn, would receive these sensor signals and pass on the data to processing applications via a connection to LAN/WiFi network or via a 4G modem, and can be installed on the nearby light poles or at significant distances from the sensors on e.g. a roof of a nearby buildings – depending on the range specification of a particular solution.
Ground parking sensors typically use one or more of detection sensors, such as magnetometer, various radars and light sensors to identify vehicle presence. Simple sensor models usually use only magnetometer – a sensor that can sense presence of a large metal object (usually the car’s engine) in it’s vicinity. While least expensive, accuracy of such sensors can be impacted by nearby large vehicles, electric current and, e.g. lack of a large metal engine in the modern EV’s . More advanced sensors compensate for these factors using additional sensor technologies such as microwave radar and light sensors.
Conceptually, the information from a ground sensor located under each car in each parking bay – is as close as one can get to the “ground (literally :)) truth” about parking space availability and, it makes the ground sensors a logical choice for per-space parking management. However, producing a reliable ground sensor solution that can both provide accurate information and withstand the exposure to weather elements and take the abuse from vehicle driving over them, has proven to be a challenging task.
First generation of modern smart parking ground sensors that hit the market about 5-7 years ago, earned a bad reputation for the ground sensors in general due to their lack of accuracy, high cost and physical integrity and moisture penetration problems. This, in part, lead to forming a general perception in the smart parking solution circles, that camera- and radar-based solutions are more reliable and less expensive choices – the perception that is still mostly in place even today.
However, over the past several years, ground sensor manufactures, including Nwave, continued to perfect and field-test their technology, while also substantially driving down the costs. Thus, as of now, this old ground-sensor reputation is no longer true, as ground sensor solutions can deliver both high detection accuracy and reliability and a very competitive cost – at least this is the case for our Nwave ground sensors.
On the privacy side, ground sensor solutions do not transmit any personal information such as license plates – vehicle identification is “anonymous” for the base occupancy solution. For the advanced functionality, sensor solutions themselves, again, do not transmit any personal data, only a set of randomized ID numbers, which can then be linked to individual cars or users in the secure payment processing or access management applications – only with the user’s explicit consent when he or she explicitly “opts in” into such services.
Going deeper into selecting the best ground sensor solution for your parking project, there is a number of additional considerations, including pro’s and con’s of surface-mount vs. in-ground (flush-mount) variations as well as choosing a particular sensor vendor and technology, since not all ground sensors are created equal. If you would like to learn more about selecting a ground parking sensor, please see our post on sensor KPI’s, which goes deeper into the factors to keep in mind for such selection.
Connected vehicles
As the world of technology moves forward, there will be more and more connected vehicles with autonomous capabilities on the road. These vehicles are equipped with a range of sensing technologies, including cameras and various combinations of radars – to detect and navigate their surroundings. From the smart-parking solution point of view, these cars carry on them a number of various “parking sensors”, that can potentially replace a need for external smart parking infrastructure. In fact, the belief (or hope) that all cars will soon be “connected”, is already used by some city planners as an excuse not to implement a smart parking solution today.
Though this may be a vision of the future, the reality is that we are still a long way away from having our vehicle fleet 100% connected. At a minimum, a large number of non-connected cars that are manufactured today, will still be on the road in 10 years. And as long as any substantial number of cars on the road remain non-connected, we cannot really replace building an “external” solution with waiting for the 100%-connected world. Technology adoption is a tricky business, nobody knows when exactly we are going to hit 100% connected vehicles on the road. But given at least my life experience and a hindsight of historical technology adoption trends, I would bet it’s not 10 years, not even 20. May be 30. In the meantime, we got our lives to live, cars to drive and to park, hopefully in the “smart way” :)
Concluding thoughts on camera-based solutions
A few concluding thoughts on camera-based solutions – in more general terms. As we already see today, acceptance of camera-based solutions is varying widely across the globe and is a part of the privacy-vs-security discussion and value balancing in each particular country. In some countries, e.g. China, camera-based solutions are a norm, with the “security” outweighing the “privacy” side of the argument. In others, e.g. Germany and most of Europe, camera-based solutions are not allowed at all due to privacy concerns. In the United States, we appear to be somewhere in between, with cameras being part of our lives but definitely not at the level seen in some of the other countries. It is the author’s personal view that, as Americans learn more about what is happening with their private data, the concern for privacy will grow in the future, and so will aversion towards camera-based solutions.
Nwave Solution advantage
Nwave’s market-leading ground sensor solution can serve as a solid foundation for your feature-rich, reliable, and cost-effective modern smart parking solution. Please refer to www.nwave.io for more details.