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The goal of this project is to develop a crowdsource-enabled smartphone app with multiple choice items and free text based on understanding and usability of green space. The project aims to facilitate better designs of green spaces by providing robust evidence on which characteristics of green space contribute to promoting healthier urban environments at individual and local levels.


Urban planners typically rely on macro-level data (e.g. census data) to develop long-term plans for urban infrastructure provision. On the other hand, crowdsourced data is growing in popularity and use, capturing information through citizen engagement to provide more localised, individual and frequent information. This opens up new possibilities for planners, enabling the detail and voices of city dwellers to be the fabric from which planning strategies are built. 

Despite the promise and potential of crowdsourced data for use in policy-making, a lack of knowledge and experience exists when combining crowdsourcing approaches with new technology platforms, such as Internet of Things (IoT), which can translate to barriers in adoption rates and relevance to stakeholders involved in the planning process.

Project Plan

The project will be delivered through a series of stakeholder workshops in order to develop, pilot and evaluate the smartphone app alongside the project partners Oxfordshire County Council, Oxford City Council and Smart Oxford, Cambridgeshire County Council and Smart Cambridge, NHS Healthy New Towns: Bicester Healthy New Town and Northstowe Healthy New.

What is Crowdsourcing?

Crowdsourcing is the practice of engaging a ‘crowd’ or group for a common goal — often innovation, problem solving, or efficiency. Crowdsourcing can take place on many different levels and across various industries. Thanks to our growing connectivity, it is now easier than ever for individuals to collectively contribute — whether with ideas, time, expertise, or funds — to a project or cause. This collective mobilization is crowdsourcing. A good example of crowdsourcing is wikipedia where the platform leverages the power of the 'crowd,' i.e. a contribution of millions of people, to generate knowledge on a global scale.

This phenomenon can provide organizations with access to new ideas and solutions, deeper consumer engagement, opportunities for co-creation, optimization of tasks, and reduced costs. The Internet and social media have brought organizations closer to their stakeholders, laying the groundwork for new ways of collaborating and creating value together like never before. 

Adapted from from:

Prototype Development

We developed a version 1 prototype of the smartphone app (eNEST) and are now moving to a version 2 app development with feedback from key stakeholders. Below show some images of the prototype version 1.

eNEST App Prototype Version 1.0 


Location detection function


Photo taking function


Sound recording function

Project Information

Project lead:

Dr Andy Hong, University of Oxford. 


Funding: Research England - Pitch-In

Project website:

Project twitter:



This project aims to develop a mobile environmental monitoring platform using Arduino and research-grade air pollution and meteorology monitoring equipment. Arduino is open-source and is flexible enough to support a variety of needs for environmental sensing. So, it is being touted as a prototyping platform for Internet of Things (IoT) development. The funding support for this project comes from the USC Research Enhancement Grant. 


It all came naturally from my own needs to develop a custom datalogger to connect different environmental monitoring devices for my dissertation project. Air pollution monitoring devices, such as TSI's DustTrak and Thermo Scientific's pDR 1500, all come with different communication protocols and software that requires transferring of data between the device and a computer. Often times, the transferring process takes several hours in addition to the time it takes to collect samples in the field. 


  • DataLogger: Arduino YUN and Arduin Uno

  • TSI DustTrak 8520: capable of measuring PM 10 or PM 2.5 concentrations in outdoor environment. The communication protocol is RS232, and uses specific command to communicate with the device.

  • TSI CPC 3007: capable of measuring much finer ultrafine particle concentrations than the P-trak. It operates with the same principle as the P-Trak, but it has faster response to freshly emitted traffic pollution, therefore, it is used widely for measuring near-road traffic pollution.

  • TSI P-Trak: capable of counting ultrafine particles in outdoor environment. It operates by drawing an aerosol sample continuously through a heated saturator, where alcohol is vaporized and diffuses into the sample stream. Isopropyl alcohol cartridge must be replaced every 3 hours depending on the ambient temperature.

  • ​​Wind direction/speed sensor: Gill WindSonic Ultrasonic Anemometer 

  • Temperature / Relative humidity sensor: Vaisala HMP50 temperature and humidity probe

What is Arduino?

Arduino is a small but powerful microcontroller (i.e. computer) that allows users to interface with a variety of electronic devices and sensors. It was originally developed by Massimo Banzi and David Cuartielles to teach their students about electronic circuit boards, but now its use has been expanded beyond the classroom.

Arduino Microprocessor

Arduino is now being used and implemented by commercial developers and engineers as a cross platform to connect and control different devices. The beauty of Arduino is that, thanks to its open-source approach, users can customize any electronic devices to suit your needs with simple lines of codes based on C programming language. There is also a huge community of developers, hobbyists, students, and researchers that help each other's projects. 

Basic Architecture
The basic architecture of the CitySensor follows a typical Internet of Things (IoT) framework. Basically, a set of sensors are connected to the central microprocessor (Arduino) through either digital channel or analog channel (Data Collection). The collected sensor data are being processed and formatted using a timestamp through the centralized microprocessor (Data Processing). The microprocessor has a 3G network communication extension which allows the processed data to be transmitted over cellular network (Data Transmission).  The transmitted data are being archived on a cloud server that runs 24 hours and 365 days (Data Storage). Users can access both the archived data and the data being streamed through the cellular network in real time. 

CitySensor IoT Architecture

Prototype Development
A prototype was developed using Arduino as a central microprocessor. The prototype successfully read both analog and digital signals. One major challenge of this project is that different devices use different communication protocols. So, it is difficult to directly connect monitoring devices to the Arduino system, and expect Arduino to automatically read the signals. Analog devices are much simpler because there are no protocol issues. But when it comes to reading digital signals, each manufacturer and even with the same manufacturer, different models use different protocols. Currently, the prototype is under development and in a testing phase. For field deployment, a weather-proof enclosure was designed. Several enclosures were considered, including water-proof NEMA enclosure and Pelican brief enclosure. NEMA 3R was chosen as the final enclosure type because of it's sturdy design and weather resistant function. See this document for the design of the NEMA 3R-based environmental enclosure.

Field Deployment
We had a series of discussion with Los Angeles Metro to pilot test the CitySensor by deploying it at various transit stations in Los Angeles. Two options have been suggested. One option was to put the device in a metal cage to provide full protection. Another option was to fix the equipment using a metal chain. For either options, deployment must be coordinated with union workers and transit police. For added security, it was suggested that the Metro place a CCTV camera to strengthen security level near the deployment area. The photos below show site visits and feasibility testing of the suggested deployment options.​

CitySensor Setup 1

Option 1: Partial Protection using a Metal Chain

CitySensor Setup 2

Option 2: Full Protection using a Metal Cage

Feasibility Assessment for Prototype Deployment at various Los Angeles Metro Stations


BikePed Analytics

This project was born out of a collaboration with UCLA and Placemeter (TM) to validate computer-vision technology for quantifying traffic information, such as pedestrian and bicycle movement, and passenger and freight vehicles.


The motivation to partner with Placemeter came while I was doing a study on the impact of CicLAvia (car-free street event) on traffic and air quality. Traditionally, we have been using pneumatic tubes and human labor to count pedestrians, bicyclists, and cars. In liue of this old technology, Placemeter offers much easier and cheaper ways to quantify traffic data which do not require any equipment installation or human labor. If this approach can be proven successful for quantifying bike/peds with higher precision, this technology has the potential to disrupt the traditional traffic engineering practice of quantifying bikes/peds/vehicles. 

One of the major challenges of this technology is to get access to city-owned CCTVs or IP cameras. New York City already opens their traffic CCTVs to the public, so Placemeter has no problem getting the traffic feeds from the city.  For the Culver City CicLAvia event, we successfully recorded traffic camera feeds. Special thanks to Gabe Garcia (traffic engineering Analyst at Culver City) who helped us get the traffic camera feeds. We have successfully turned the traffic videos into valuable traffic count data. In the case of Los Angeles, however, there is no publicly available CCTV camera feeds, so we had to get permission from LA Department of Transportation to get access to their traffic feeds. It turns out that they have legal and security issues with regard to plugging any device to their system. So, we couldn't use Placemeter technology for our project. In the future, if many cities adopt internet-connected CCTV cameras and made them available publicly, Placemeter technology has a bright future. At the moment, the legal and security hurdles in getting access to city-owned traffic feeds are the major barriers to this new technology.

What is Placemeter?

Placemeter is a company based in New York City that develops computer vision algorithm to offer users with convenient ways to quantify foot, bike, and vehicle traffic. They process video feeds from CCTV cameras, and their algorithm detects pedestrians, bicyclists, and vehicles with an accuracy of close to 90%. 


The computer vision algorithm was developed a long time ago around 60s, but what's unique about Placemeter is that they provide very convenient front-end user interface to monitor traffic in realtime. They also allow users to record video feeds using their smart phones and use that video to quantify traffic information. 

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