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

  1. 1. 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
  2. 2. How can real-world services, offered by urban sensors, be used by mobile users to shape their everyday lives? Impact of remote mobile sensing? Design aspects of mobile apps? How to extract significant information from raw data provided by hundreds of sensors deployed nearby the user?
  3. 3. UrbanRadar Mobile App Temperature Humidity Wind Luminosity Air Quality Noise Weather Forecast
  4. 4. Urban Mashups
  5. 5. Extended Urban Mashups
  6. 6. Case Study Two-week period 13 Users Two mini focus groups 6 Undergraduate Students 7 Postgraduate Students
  7. 7. Case Study 6 Undergraduate Students 7 Postgraduate Students Frequency of use: once per day Frequency of use: once per day More engaged with the app Less engaged – more busy Popular services: weather forecast, temperature, wind, air quality, humidity Popular services: weather forecast, temperature, wind Motivation: health, curiosity, work entertainment, Motivation: curiosity, safety, work, sports Activities: housework, personal care, others (car wash) Activities: housework, leisure, personal care
  8. 8. 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
  9. 9. Case Study 6 Undergraduate Students 7 Postgraduate Students “Useful due to dangers around us” “Useful for outdoor activities” “Helps to engage with the physical environment” “First-aid box” “Understanding of pollution may create some anxiety” “A stimuli for a long-term change” “Being informed is the first step of change” “It depends on the way you receive this information” “The application should engage with the user, and not the opposite” “Move from informing to suggesting”
  10. 10. Design Principles 1. Personalization and User Profiling 2. Notifications and Alerting 3. Guidelines and Recommendations
  11. 11. Design Principles 4. Forecasting and Predictions 5. Accuracy and Reliability 6. Meaningful Information
  12. 12. Design Principles 7. Easy creation of Rules 8. Visualizations 9. Comparative feedback
  13. 13. Design Principles 10. Locating the Source of the Problem 11. EcoVisualizations
  14. 14. Larger case study More users Longer period More devices/services Better analysis Case Study Design Principles
  15. 15. Thank You! Andreas Kamilaris email: camel9@gmail.com

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