Yeung lam - UCLA Center for Embedded Networked Sensing
Dr. William Kaiser - UCLA Center for Embedded Networked Sensing
Dr. Thanos Stathopoulous - UCLA Center for Embedded Networked Sensing
Many systems monitor parking lot occupancy, but require installation during the construction of the structure. Systems implemented in existing lots typically require complex installation. Additionally, the information captured by these systems is typically confined to the structures in which it is captured. We have the ability to archive this data, but no central or uniform data access protocol exists.
We implemented a low-cost, easy-to-install parking lot occupancy monitoring system that integrates with an online database to provide parking space information locally and remotely. This system provides incoming cars information about parking availability with online access using computers and cell phones.
We created this system to give parking lot patrons access to information to help them efficiently choose a parking strategy. We also needed to provide data for parking administrators to aid them in effectively managing parking resources. The initial deployment site was a level of the UCLA medical building parking lot that would benefit from our application because it is subdivided into two zones, one for patients and another for staff and patients.
To deliver useful information to parking patrons, the system provides an overall occupancy count for the parking structure as well as more detailed zone-level information. We placed sensors at each entrance, exit, and transition points between the zones. Sensors at the entrance and exit points wirelessly transmit data on entering and exiting vehicles to a central base station at the exit kiosk. Sensors monitoring the transition points between zones detect traffic and direction to determine if vehicles are moving between zones. The sensors send this data to the central base station, which analyzes all incoming data to give a real-time count of total available parking spots and counts for each zone.
Hardware System Design
We use passive infrared (PIR) sensors from Parallax Technologies as our primary vehicle traffic detectors. These sensors detect changes in the infrared black body radiation emitted by objects and require little power because detection occurs without any excitation. They also provide a digital output that can be configured to output pulses during continued motion detection, or remain high during continued motion detection and drop to low after reaching equilibrium.
Wireless Sensor Nodes
To develop our system, we used three NI WSN-3202 analog input nodes, each equipped with four analog voltage inputs and four digital I/O. We connected the PIR sensor module outputs to a digital input, and the sensor batteries to an analog input to monitor power consumption. In addition, we used four AA batteries to power the WSN nodes. Even though we could have constantly transmitted raw sensor data to the base station, we used the processing capabilities of the nodes to locally compute entrance and exit events and limit radio transmission to the base station. The node can decide locally when a car has passed rather than sending raw data to a server for processing. By adding this capability, the node only has to transmit messages when a car is detected, which increases the battery life.
An NI cRIO-9014 embedded real-time controller, powered by an AC source, made up the base station in one of the two exit kiosks of the parking structure. We connected the station via Ethernet to the UCLA transportation network. Because of UCLA transportation security policies, the data is inaccessible outside of this network, but we can access our backend database server for data storage.
With the NI WSN-9791 Ethernet gateway, we facilitated communication between the CompactRIO base station and the wireless sensor nodes. We installed this gateway inside the exit kiosk adjacent to the kiosk in which we housed the CompactRIO controller. An AC wall source powers the station and is connected to the same network as CompactRIO.
Online Data Repository
We stream the data from CompactRIO in real time to the sensorbase.org data repository, which provides a user-friendly Web interface to download, browse, share, and organize data. In addition, this repository provides a Web service application layer used to develop customized Web pages for presenting parking lot information to computer and cell phone users.
First, the wireless sensor nodes sample data from the PIR modules. The node runs a custom VI programmed using the NI LabVIEW Wireless Sensor Network (WSN) Module Pioneer that utilizes the digital I/O notification feature of the WSN node. When motion is detected by the PIR module, this event is triggered and the WSN node continues to sample the digital input until it drops back to low. After an event is detected, the WSN node sends a radio message back to the CompactRIO base station indicating that the event occurred and its length of time. By using the digital I/O notification system and performing analog sampling at a very low rate, we minimize the amount of time we have to keep the WSN nodes turned on to send data.
The pulse-length data from the WSN nodes is sent to the CompactRIO base station and categorized by the length of time it took the object to pass by the sensor to determine if one or more cars have passed or if a pedestrian has passed. CompactRIO keeps an internal count of the total number of cars present in the parking garage. After each exit or entrance event, the event data and the total count are logged internally to a file on the CompactRIO flash storage and uploaded to the sensorbase.org data repository.
We are currently sending the system data to the sensorbase.org data repository for browsing, downloading, and graphing through the built-in Web interface. Data is also exposed to custom Web applications through a Web services layer. We built a simple Web interface using these Web services to graph the data over a certain time period and provide the total count of cars currently in the parking garage.
In addition to vehicle detection data, we set each WSN node to sample one analog channel every 10 minutes to gauge the sensor’s battery use. Then we transmitted battery and link quality data to the base station and logged and uploaded it to the database. We also created a simple Web interface to provide information on the health of the system for our users.
Future System Enhancements
After the initial installation, we want to enhance the system so that the base stations can upload information as well as download data from other “linked” parking lots to help the users choose a parking lot if the one they are in is full. The primary target for expanded deployment would be the same parking level of the medical building as well as the adjacent parking structure. All of the lot information will be available online and onsite signs can inform patrons of the parking availability at nearby lots.
We also plan to install LED display signs in the parking structures. The displays will automatically update to provide incoming cars with information on parking space availability rather than using signs manually placed by parking attendants.
Moreover, we took advantage of the NI WSN platform to make monitoring of parking structure occupancy economically feasible and eliminate the need for a hardwired system.
UCLA Center for Embedded Networked Sensing