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
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?
UrbanRadar Mobile App
Temperature Humidity Wind Luminosity Air Quality
Noise Weather Forecast
Urban Mashups
Extended Urban Mashups
Case Study
Two mini focus groups
Two-weekperiod13 Users
6 Undergraduate Students
7 Postgraduate Students
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
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
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”
Design Principles
1. Personalization and User Profiling
2. Notifications and Alerting
3. Guidelines and Recommendations
Design Principles
4. Forecasting and Predictions
5. Accuracy and Reliability
6. Meaningful Information
Design Principles
7. Easy creation of Rules
8. Visualizations
9. Comparative feedback
Design Principles
10. Locating the Source of the Problem
11. Eco-Visualizations
Case Study
Design Principles
Larger case study
More users
Longer period
More devices/services
Better analysis
Andreas Kamilarisemail: [email protected]
Thank You!