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The Impact of Remote Sensing on the Everyday Lives of Mobile Users in Urban Areas Andreas Kamilaris and Andreas Pitsillides ICMU 2014, Singapore 8 January 2014

The Impact of Remote Sensing on the Everyday Lives of Mobile Users in Urban Areas

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Increasing urbanism creates serious ambient problems that downgrade the quality of life of citizens. Environmental awareness may help people to take more informed decisions in their everyday lives, ensuring their health and safety. The Web of Things is becoming a reality, as embedded sensors are being deployed in urban areas for environmental monitoring. These sensors are accessible and discoverable through the Web, and their services can be harnessed by mobile users on the go. In this presentation, we perform a small case study, by using mini focus groups, to identify the impact of remote sensing on the everyday lives of users. By means of UrbanRadar, an application that discovers and interacts with environmental services offered by Web-enabled urban sensors, we investigate and discuss the acceptance, influence, usefulness and potential of these services to mobile users. Finally, based on the feedback from participants, we identify eleven design patterns, important for future mobile applications involving remote sensing. This presentation is based on the following research paper: Andreas Kamilaris and Andreas Pitsillides. The Impact of Remote Sensing on the Everyday Lives of Mobile Users in Urban Areas. In Proc. of the 7th International Conference on Mobile Computing and Ubiquitous Networking (ICMU), Singapore, January 2014. (online at: http://www.cs.ucy.ac.cy/~akamil01/papers/kamilaris_urban_casestudy.pdf)

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Page 1: The Impact of Remote Sensing on the Everyday Lives of Mobile Users in Urban Areas

The Impact of Remote Sensing on the Everyday Lives of Mobile

Users in Urban Areas

Andreas Kamilaris and Andreas Pitsillides

ICMU 2014, Singapore 8 January 2014

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How can real-world services, offered by urban sensors, be used by mobile users to shape their everyday lives?

How to extract significant information from raw data provided by hundreds of sensors deployed nearby the user?

Impact of remote mobile sensing?

Design aspects of mobile apps?

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UrbanRadar Mobile App

Temperature Humidity Wind Luminosity Air Quality

Noise Weather Forecast

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Urban Mashups

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Extended Urban Mashups

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Case Study

Two mini focus groups

Two-weekperiod13 Users

6 Undergraduate Students

7 Postgraduate Students

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Case Study

6 Undergraduate Students

7 Postgraduate Students

More engaged with the app

Motivation: health, curiosity, work entertainment,

Motivation: curiosity, safety, work, sports

Activities: housework, personal care, others (car wash)

Activities: housework, leisure, personal care

Frequency of use: once per day Frequency of use: once per day

Less engaged – more busy

Popular services: weather forecast, temperature, wind, air quality, humidity

Popular services: weather forecast, temperature, wind

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Case Study

Urban Mashups

Event Services employed

Asthma Air Quality, Humidity

Leisure trip Temperature, Wind

Football playing Temperature, Humidity

Comfort level Temperature, Humidity

Good weather indicator Temperature, Wind

Personal weather monitor Temperature, Weather Forecast

Going to the beach Temperature, Weather Forecast, Wind

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Case Study

6 Undergraduate Students

7 Postgraduate Students

“Helps to engage with the physical environment”

“Useful due to dangers around us” “Useful for outdoor activities”

“First-aid box”

“A stimuli for a long-term change”“Understanding of pollution may create some anxiety”

“Being informed is the first step of change”

“It depends on the way you receive this information”

“Move from informing to suggesting”“The application should engage with the user, and not the opposite”

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Design Principles

1. Personalization and User Profiling

2. Notifications and Alerting

3. Guidelines and Recommendations

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Design Principles

4. Forecasting and Predictions

5. Accuracy and Reliability

6. Meaningful Information

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Design Principles

7. Easy creation of Rules

8. Visualizations

9. Comparative feedback

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Design Principles

10. Locating the Source of the Problem

11. Eco-Visualizations

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Case Study

Design Principles

Larger case study

More users

Longer period

More devices/services

Better analysis

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Andreas Kamilarisemail: [email protected]

Thank You!