A smart city solution: Time-Meter

Idea behind the project:

If you live in congested cities where street parking is hard to come across you wish to be notified if there are any parking spots in your destination. Additionally, even though credit card meters are more modern than coin meters both solutions are falling behind in comparison with new technologies. Time-Meter looks to tackle both problems within one solution.

With the move towards smart cities, we are looking to have our city interact with its inhabitants to help them make smarter decisions while also improving their quality of life. Not having coins to pay a coin only meter can be quite frustrating. As presented in https://www.transalt.org/ , 45 percent of the traffic in Manhattan is generated by cars circling the block looking for parking . Time-Meter provides updates to those near by on available meter locations, along with its parking restrictions and regulations. On her MIT Technology Review article, Erika Jonietz describe that in a study conducted in 2006 by Donald Shoup, a professor in the department of urban planning at the University of California, Los Angeles, it was calculated that, over the course of a year, vehicles looking for parking in one small business district of Los Angeles burned 47,000 gallons of gasoline and produced 730 tons of carbon dioxide.

Following the above numbers, Smart-Meter would also help reduce emissions while also reducing car wear and tear. Having sensor data that captures how long drivers are using the spots for, how many cars in a given day use a given spot and overall “car” traffic on the meter area can help a city better plan new roads, approve building and development projects and also better design public transportation routes.

Honk App — no sensor data used.

Why design a smart meter?

Using as a guide the discussion on smart cars, it is clear that long term transportation will be revolutionized. Individual car ownership might not be a common item of the future and smart cars would be able to connect one another providing updates on both traffic and available parking spots. This infrastructure will take time to be developed and a strong foundation on data, understanding our roads and space usage will be key for a successful smart cities and smart mobility future. Time-Meter helps solve the present problem while also gathering data that can help pave the future.

Implementation and technologies:

The prototype can be designed using a Raspberry Pi or an Intel Edison board. While infra red beam technology would be the most appropriate to be used given its long range, we decided to opt for a still effective but less expensive approach with ultrasound sensors. The sensors algorithm to identify cars using ultrasound sensors can be refined to rule out other objects such as people walking by, trees and other larger objects. It was discussed using RTT (round trip time) to identify where each sensor and meter is in the map. The idea was to lower the cost my having just a handful of Time-Meter’s in a given row have a GPS sensor that provides the coordinate location ( accuracy of 3 meters) while we could estimate the location of the other Time-Meter’s using the RTT it takes to connect from one meter to the next. While this approach is cost saving, it is not accurate and can lead into providing incorrect location data. Additionally we had discussed hard coding the coordinates on each meter as a static value that can be passed on each package sent. It was decided that including a GPS module on each Time-Meter would be a good approach to provide more accurate location data. Both the GPS and ultrasonic data will be collected and posted to a cloud solution. With the use of a LoRa WAN transceiver we can make use of a LoRaWAN gateway and further use the nodes to relay data across its peers. The information can then be posted in graphing dashboards such as Graphite or Graphana to analyze patterns such as high usage windows that users should avoid. Additionally, the information can be used to create maps which illustrate areas with less parking available and pin point specific open parking spots.

Integrating real-time information, such as traffic data, into ArcGIS maps and apps. From esri.com

A user would be driving in a given area, through the GPS localization in the user’s phone along with the GPS sensor in Time-Meter it would find the available spots in the area and provide the results to the user. The user would then utilize an RFID tag identification that would be used for easy payment; meaning the RFID tag would identify the payer removing the need to deposit coins or swipe a credit card. RFID tags could also be used to mark and validate disable parking spots.

Future implantation:

- We believe that there are even more applications that can be via Time-Meter such as emergency relive path guidance. With the use of LED lights, the meters can connect to the city’s alert systems when there are natural disasters. The idea would be to illuminate the path to safety by utilizing the meter.

- On a data aspect, the sensor data collected could be utilized by city officials to better plan new roads and improve overall traffic flow.

- Additional sensors could be added to Time-Meter that would provide air quality. This would help monitor and track air throughout the city given that the meters are across multiple neighborhoods.

- Through Google maps implementation Time-Meter could connect to the end user while on route to its destination and help find / predict an open spot when arriving to destination.

- We are considering using IOTA both as a block chain solution to share data across LoRA and cross cities, but also as a crypto currency payment method. We are still evaluating the effectiveness and need of having block chain as part of this solution and the cost in its adoption.

IOTA stack
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