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

Andreas Kamilaris and Andreas PitsillidesNetworks Research Laboratory, Department of Computer Science

University of Cyprus, Nicosia, CyprusEmail: kami@cs.ucy.ac.cy, andreas.pitsillides@ucy.ac.cy

Abstract—Increasing urbanism creates serious ambient prob-lems that downgrade the quality of life of citizens. Environmentalawareness may help people to take more informed decisionsin their everyday lives, ensuring their health and safety. TheWeb of Things is becoming a reality, as embedded sensors arebeing 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 paper, we perform a small case study, by using minifocus groups, to identify the impact of remote sensing on theeveryday lives of users. By means of UrbanRadar, an applicationthat discovers and interacts with environmental services offeredby Web-enabled urban sensors, we investigate and discuss theacceptance, influence, usefulness and potential of these servicesto mobile users. Finally, based on the feedback from participants,we identify eleven design patterns, important for future mobileapplications involving remote sensing.

Keywords—Urban Computing; Remote Sensing; Mobile Comput-ing; Case Study; Design Patterns; Web of Things.

I. INTRODUCTION

Urban environments are becoming largely crowded, hostingmore citizens than they are able to support. Already, urbanareas host around 50% of the world’s population and the cities’population is expected to double in the next 40 years [1]. Theincreasing urbanism implies negative effects to the people andthe city as a whole. Traffic is heavily increased and levelsof pollution are rising. Some areas become really dirty whilehealth and security are compromised.

Urban environments are becoming equipped with miniatur-ized sensors, measuring with high precision the local envi-ronmental conditions. Sensor devices already support a largevariety of sensory services such as temperature, humidity,radiation, electromagnetism, noise, chemicals etc. The Internetof Things (IoT) [2] includes architectures and technologiesthat allow the Internet to penetrate into the real world of thesesensor devices. IPv6 and the efforts for porting the IP stack onembedded devices [3] facilitate the introduction of the Internetin pervasive urban computing.

Recent advances enable sensor devices to operate as tinyWeb servers, being able to expose their capabilities as Webservices [4]. Therefore, the information gathered by differentsensors can be shared by means of open Web standards,realizing the vision of a Web of Things (WoT) [5]. As theWeb has penetrated deeply in our everyday lives, it can beused as the platform for supporting environmental monitoring.

This presence of Web-enabled sensors in urban areas, needsto be harnessed toward benefiting people. Monitoring ofphysical conditions can help people to ensure their healthand security, and also save time by making more informeddecisions, such as avoiding congested regions when driving.People could acquire more sustainable lifestyles, when they areinformed about the impact of their actions on the environment.

Though we assume that mobile remote sensing can beharnessed for the benefit of citizens, we still cannot tell withconfidence whether and how these pervasive environmentalservices, offered by urban sensors, would be used by peopleto shape their everyday lives. Extracting significant and usefulinformation from raw data provided by hundreds or thousandsof sensor devices deployed nearby the mobile user is anopen problem. In this paper, we aim to study these researchquestions, by performing a small case study that observes theuse of some environmental services by students at a universitycampus, recording their feedback and impressions.

The rest of the paper is organized as follows: in SectionII we identify related work and in Section III we presentthe development of UrbanRadar, a mobile application thatdiscovers and interacts with sensor devices deployed in thevicinity of the user. Then, in Section IV we explain themethodology of our case study while in Section V we describethe feedback from our focus groups. Afterwards, in Section VIwe discuss the general findings of the case study and, finally,in Section VII we conclude the paper and discuss future work.

II. RELATED WORK

Our approach spans in the research domains of location-based services and urban computing, in regard to mobileremote sensing. Location-based services make use of geo-graphical positioning services, provided by mobile devices,to perform some advanced tasks such as smart navigation,travel assistance etc. Positioning sources may be the GlobalPositioning System (GPS) or local network services (e.g. GSMCell ID, Wi-Fi fingerprinting, DHCPs GeoConf).

Urban computing is an emerging research area that focuseson the use of technology in public environments such ascities, parks and suburbs and their interaction possibilities withhumans. Various projects have used remote sensing to improvethe lives of citizens. Kostakos et al. [6] use a Bluetooth-basedinfrastructure to identify characteristics of urban environmentssuch as mobility patterns, social and spatial structures etc.

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Ubiquitous Oulu1 is a prototype of a future city, in which betterservices are offered to the people, by embedding informationtechnology into the urban environment in an invisible way.

A special area of urban computing is mobile participatorysensing, involving the tasking of mobile devices to forminteractive, participatory sensing systems that enable individ-uals in the general public to gather, analyze and share localknowledge. The MetroSense project [7] aims at transformingthe mobile device into a social sensing platform. Goldman etal. [8] show the significance of participatory sensing for ourdaily lives and its impact on climatic change. GPS-equippedmobile phones are used to photograph diesel trucks, in order tounderstand air pollution. In the NoiseTube project [9], mobilephones are used as noise sensors, to measure the personalexposure of citizens to noise, in their everyday environment.

Mobile remote sensing through the Web, is used as well forinforming the citizens about local environmental conditions.The Common Sense project [10] derives design principles fordescribing data collection and knowledge generation from re-mote air quality data. PachuRadar [11] is a mobile applicationinforming the user about local Web-based sensing services.

Related work indicates that mobile sensing, both participa-tory and remote, is beneficial to the users and engages themin sustainable actions that improve their community. However,the aforementioned studies focus on specific sensing scenarios,in which users have a direct incentive to participate, eitherbecause they experience health issues [10], or since they aresensitive about the environment and want to take actions toprotect it [8], [9], or for entertainment and sports [7].

This paper develops a more general case study, aiming toexplore whether and how environmental services are useful tothe people in their everyday lives, which are their needs andexpectations, as well as the potential of mobile environmentalmonitoring in the future. The findings from our mini focusgroups can be used to shape future initiatives involving mobilesensing in the research area of urban computing. This studyis novel in the sense that users do not have strong incentivesto participate, unlike related work [7], [8], [9], [10], hence itis interesting to capture their general, unbiased impressionstowards mobile remote sensing.

III. URBANRADAR: A MOBILE APPLICATION FORURBAN COMPUTING

UrbanRadar is a mobile application that locates and interactswith services, provided by sensors deployed near the mobileuser. It is implemented for Android phones, and it is a succes-sor of PachuRadar2, which targeted Nokia mobile devices.

The exact user location can be inferred from GPS servicesand Wi-Fi positioning. Proximity is defined as a circle withthe user’s location at the center. The radius can range fromsome meters to a few kilometers. In highly dense areas suchas big cities, a radius of tens of meters can be enough while insuburbs this radius can cover hundreds or thousands of meters.

Figure 1 illustrates the operation of UrbanRadar. The mobilephone represents the user’s position and the red circle indicates

1http://www.ubioulu.fi/en/home2http://apps.pachube.com/pachuRadar/

the area of interest, in which the user can be informed aboutsensory services. According to the figure, one sensor deviceexists in this covered area, with which the user can interactand be informed about its sensing services.

Fig. 1. UrbanRadar operation.

Web-enabled sensor devices can be deployed in urban areaswhen governmental or private organizations, companies andcitizens expose their sensory services through open, Web API.High interoperability between heterogeneous physical devicescan be achieved by following Web principles [5].

A. Sensor DiscoveryStandard Web protocols for real-time sensor discovery or

even a search engine for the WoT are currently unavailable.Early efforts towards this direction include Dyser [12] andSnoogle [13], as real-time search systems for physical entitiessuch as sensor devices. Harnessing the DNS system as a searchengine for the real world can be a promising practice [14].

Until such efforts become more popular, accepted andstandardized, online global sensor directories can be employedfor sensor discovery. One of the most well-known directoriesavailable today is Xively3 (former Pachube or Cosm).

Xively enables people to share, discover and monitor envi-ronmental data from sensors connected to the Web, globallyand in real-time. We used Xively as a platform for discoveringand interacting with sensor devices through the Web, becauseit has a clean Web API with advanced services for developers.Besides, it is currently quite popular, being employed bythousands of people and companies worldwide.

B. Urban MashupsExposing the functionality offered by sensor devices as Web

services, allows the development of Web mashups involvingreal entities. In this case, Web mashups are extended intophysical mashups [15], combining sensory services using theclassic techniques of Web mashups. Physical mashups cannotbe directly applied in urban environments, since these denseareas are characterized by high mobility and unpredictability.

Thus, in order to adapt to these highly dynamic landscapes,we define urban mashups as opportunistic physical mashups,

3https://xively.com/

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validated only when the local environmental conditions supportthe sensor-based Web services defined by these mashups.Urban mashups are service-centric, focusing on the servicesoffered by sensor devices and not on the devices themselves.This happens because a large number of similar sensor devicesmay be deployed inside some area, offering the same service.

UrbanRadar includes support for urban mashups, allowingusers to combine environmental services together, using oper-ations such as greater than, if/then, and/or, etc. An exampleurban mashup is displayed in Figure 2. In this example, asensor measuring the levels of noise, a pollution sensor anda street camera combine their services in order to infer thetraffic conditions existing at a city’s center. Urban mashupscan be combined and reused, forming directed acyclic graphs.For example, the example mashup can be extended to suggestto the user whether to take the bicycle for commuting, in casetraffic and weather conditions are appropriate.

Fig. 2. An example urban mashup.

Users need to specify if the real-world services that pro-duce each event, must be perceived as low/average/high (forservices such as temperature, humidity) or good/average/bad(for services such as weather, air quality). It is more convenientto select easy-to-understand keywords than complex measure-ments (e.g. decibels for noice, miles per hour for wind).

In addition, users have the option to select weights for eachenvironmental service, if for example street occupancy affectstraffic more significantly than noise. However, this possibilityis only for advanced users, since it is difficult for novice usersto properly define these weights. We left this feature out ofthe case study described in the following sections.

IV. METHODOLOGY

To assess the impact of the WoT on mobile users, we neededto simulate a digital city in a controllable environment. Weselected the campus of the University of Cyprus as our focusarea, targeting students as the subjects of our case study.

We deployed various sensor devices, offering a numberof environmental services to the students. These services arelisted in Table I. We used two different types of sensor devices,

Telosb sensor motes4 and Sensaris ECOsense pods5.Real services involved sensor devices deployed at the cam-

pus while Web-based services employed information availableon the Web. The measurements of the real services and theinformation from the Web-based services were forwarded tothe Xively platform through a local gateway server every 10minutes. Thus, users could discover and be informed aboutthese services through UrbanRadar.

Our study aims to address the following research questions:• Are environmental services useful in the everyday life of

people? How can one combine environmental servicesto produce more meaningful real-life events?

• Can real-world services influence and improve thelifestyles of people and how?

• Can these services raise the awareness about the envi-ronment and motivate citizens to respect their cities?

• Which are the needs of people regarding real-world data?• Which is the potential of mobile remote sensing in

coming years and what do people expect to see?

V. FOCUS GROUPS ANALYSIS

We recruited 13 students to participate in our study, askingthem to install UrbanRadar on their mobile phones and usethe application for two weeks. We created two semi-structuredmini focus group sessions [16], divided in two categories: a)undergraduade students (6 people, 2 male - 4 female, 18-24years old) and b) postgraduade students (7 people, 3 male - 4female, 25-30 years old). We will refer to the former group asyounger students and to the latter as older students.

The sessions were organized in two phases, directed byan objective interviewer while minutes were recorded by anobserver. The first phase consisted of a structured discus-sion around the use of UrbanRadar, aiming to record theimpressions of the participants. The second phase involved freebrainstorming, in which the groups were encouraged to discussabout the research questions of the study, suggesting ways ofimproving their everyday lives through environmental services,commenting on the potential of mobile remote sensing. Eachsession lasted one hour and was audio-recorded.

A. Phase A: Use of UrbanRadarThe specific environmental services used by the students

during the two weeks are listed in Table II. Some serviceswere more popular (e.g. temperature, weather forecast), whilesome others proved to be not so useful (e.g. noise, luminosity).Both younger and older students had similar preferences inregard to service use. Obviously, weather conditions were mostsignificant to them, as they directly influence their everydaylives (e.g. transportation, outdour activities, home heating).Students underestimated some services that affect importantlytheir lives as well (e.g. air quality), perhaps since this impactis not in a tangible or direct way.

Considering frequency of use, most people interacted withUrbanRadar once per day (4 younger, 4 older students), usually

4http://www.willow.co.uk/TelosB Datasheet.pdf5http://www.sensaris.com/products/senspod/

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TABLE I. LIST OF ENVIRONMENTAL SERVICES.

No. Service Name Description Service Type Device Type1 Temperature Temperature in Celsium degrees Real Telosb sensor mote2 Humidity Percentage of humidity in the area Real Telosb sensor mote3 Luminosity Relative luminosity (UVA, UVB, UVC) Real Sensaris ECOsense4 Air Quality Quality of ambient air (ozone, carbon monoxide and dioxide, nitrogen oxide) Real Sensaris ECOsense5 Noise Levels of noise in decibels Real Sensaris ECOsense6 Wind Wind speed in miles per hour and direction Web http://www.windfinder.com/7 Weather Forecast Weather conditions (sunny, cloudy, rainy etc.) Web http://www.accuweather.com/

TABLE II. USE OF ENVIRONMENTAL SERVICES.

No. Service Younger Students Older Students1 Weather Forecast 6 62 Temperature 6 63 Wind 3 34 Air Quality 3 25 Humidity 3 06 Noise 1 07 Luminosity 0 1

in the morning while preparing for their lectures. Some usersused UrbanRadar even more often (e.g. every 5-6 hours),mostly to be informed about current temperature and weatherconditions (3 younger, 1 older students). Less popular serviceswere used mostly once a week (e.g. wind, air quality, noise),mainly from curiosity (3 younger, 4 older students). In general,younger students were more engaged with the mobile applica-tion, showing a greater interest for the provided environmentalservices. This is partly explained by the fact that older studentswere more ”busy” with their work during the study.

It is interesting to see the reasons for using each service.As mentioned before, curiosity was a dominant reason (4younger, 5 older students), especially for services difficult tobe measured and perceived otherwise (e.g. wind, air quality,noise). Services such as humidity and air quality were usedfor health reasons (3 younger, 1 older students). In partic-ular, two younger students ”wanted to be informed due tohaving bronchial asthma”. Entertainment was another reason,as weather and temperature conditions could affect outdooractivities (5 younger, 1 older students). Two older studentsspecified safety as a reason, in relation to the weather forecast.They aimed to ”avoid dangerous situations such as heavy rain,storms or fog”. In addition, sport activities like cycling andswimming motivated the use of services such as temperatureand wind (1 younger, 3 older students). Finally, a reasondeclared by many students is work6 (4 younger, 4 olderstudents). As a younger student pointed out, ”being informedabout the wind is important as I need to climb scaffolding”.

Some particular activities associated with the use of the sup-ported environmental services included housework (laundry,cloth drying, gardening), leisure (playing football, jogging,swimming, cycling, walking), personal care (dressing, haircombing) and others (car washing). Dressing and swimmingwere the most popular activities noted by the users.

Finally, we asked the users whether they used the featureof creating urban mashups, in order to combine environmen-tal services together, towards more advanced events. Their

6Older students mostly work at the university performing research whilesome younger students work part-time for covering some of their expenses.

TABLE III. URBAN MASHUPS CREATED BY THE USERS.

Event Services employedAsthma Air Quality, Humidity

Leisure trip Temperature, WindFootball playing Temperature, Humidity

Comfort level Temperature, HumidityGood weather indicator Temperature, Wind

Personal weather monitor Temperature, Weather ForecastGoing to the beach Temperature, Weather Forecast, Wind

mashups are shown in Table III, listing the description of eachmashup and services involved. Seven users (57%, 2 younger, 4older students) did not use this feature at all. They preferred tobe informed about each service individually. The mashups areconsistent with the preference and frequency of use of eachservice, involving mostly temperature and weather forecast.

B. Phase B: Impact and Potential of UrbanRadarThis phase included an open discussion, in which the groups

argued about the influence, usefulness, potential and impact ofmobile remote sensing to the everyday lives of people.

1) Usefulness and Influence: Both groups recognized theusefulness of UrbanRadar in their everyday lives. Youngerstudents explained its need due to the physical dangers lurkingaround us (dust, radiation, storms, winds) while older studentsassociated its usefulness with outdoor activities for work andleisure, as well as for reasons of health or mobility in the city.An older student mentioned that UrbanRadar can be comparedto a ”first-aid box”, which helps to ensure a better qualityof life. It is notable that all users recognized that the useof a mobile application for remote sensing helped them toengage with the physical environment, since mobile phones areintegrated in their everyday lives, ”using them all the time”.

Users stated that environmental services through mobileapplications may influence positively their lives, as this aware-ness can improve their living and working conditions. Ayounger student, however, warned that ”the understanding ofpollution may create some anxiety” but all younger studentsagreed that ”the positive outcomes exceed the negatives” and”it is worth taking the risks”. Older students envisioned abroad influence of this practice, describing it as ”a stimuli fora long-term change” of the society towards sustainability.

Discussing in detail about the possible change on thelifestyles of people, users said that environmental servicescould offer better preparation and programming of activites.A younger student suggested a nice future use of UrbanRadar,for ”renting flats in areas of low humidity, pollution or radia-tion”, while another younger student mentioned that ”weatherforecasting could be life-saving for outdoor activities”.

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2) Environmental Awareness: Concerning whether mobileremote sensing can increase environmental awareness, youngerstudents were mostly positive since ”measuring and compar-ing may lead to improvement of physical spaces”. In otherwords, a competition between areas would raise the awarenessof citizens. A student argued that ”maybe I wouldn’t takethe car for small trips if I knew the impact on the envi-ronment”. However, another student posed a counter-examplethat ”good weather could encourage a trip with the car”.Older students were more sceptical, expressing some concernswhether knowledge would help people become more sensitive.The general consensus was that ”it depends on the way youreceive this information”. Obviously, older students needed toadd more meaning or purpose on the services e.g. their directimpact on the environment or ways to improve the situation.

The discussion then moved on the topic of whether real-world services can motivate people to respect their cities.Younger students were positive again, explaining that ”beinginformed is the first step of change. If noise and pollutionare high, people would then try to improve them”. Studentsrecognized that ”people tend to mimic others” and that ”bystarting sustainable actions, others will follow”, noting that”inactivity does not help”. An interesting view of a youngerstudent is that ”environmentalism can be extended to a coolstyle or vogue”. Once more, older students were a bit sceptical,and did not like the word ”respect”, commenting that ”it isnot a matter of respect, but a matter of change”.

3) Potential: For the future, students ask for timely alertingabout hazards such as fires and earthquakes. They expect to seemore environmental services in their everyday lives like dust,water pollution, radiation, and dangerous chemicals and heavymetals in foods. Older students require such mobile applica-tions to recommend solutions either for safety (e.g. actionsin case of an earthquake, alternative routes while driving incase of fire) or for health (e.g. avoid polluted areas/streets,swimming in contaminated waters). It was mentioned that”these applications must move from informing to suggesting”.

Both user groups demand reliable information, whileyounger students envision faster and more accurate forecasting.A younger student recognized the importance of ”identifyingthe source of evil”, e.g. to understand what and how it causespollution in the city. Pollution coloring [10] was suggested as acool feature to help perceive polluted areas and avoid them. Anolder student was worried about the accuracy of measurements,as people could become dependent on them in the future. Hestressed the danger of altering this data for personal benefit,e.g. to downgrade some area as polluted or vice-versa.

An important feature discussed mostly by older studentsis personalization and profiling. Students expect from theapplication to observe their needs and preferences, and adjustaccordingly its operation. An older student envisions Urban-Radar as a personal assistant, which would ”suggest outdooractivities based on weather conditions” or even ”assist athletesto improve their performance”. Social comparison with theenvironmental conditions in the areas of friends and relativesconstitutes another desirable feature, suggested by anotherolder student. In general, normative social influence has a largeimpact on people for raising their awareness [17].

Another issue stressed by participants is the need for helpfulnotifications and personalized alerts. Students agree on thepossibility of losing interest after some time, as this is thenorm in feedback systems [18]. Alerts could avert this effect.As a younger student commented, ”the application shouldengage with the user, and not the opposite”. Most studentswanted to be notified in case of abnormalities or dangeroussituations, through urban mashups. An older student asked formore control over mashup creation (e.g. defining ranges ofmeasurements, more complex rules). However, some studentsclaimed they preferred simpler operations, only in a few clicks.

Finally, younger students discussed that -as life becomesfaster and more demanding- it would be better if remotesensing was more ubiquitous in our everyday lives. A studentsuggested the use of a ”bracelet that changes colors accordingto the current measurements of environmental services”. Per-vasive visualizations could be adapted as well ”on eyeglasses”,like the Google Glass project7, or ”on the car’s windshield”.

VI. DISCUSSION

In general, both focus groups developed a fruitful discus-sion with interesting outcomes. Younger students were moreenthusiastic, while older students more cautious.

As some older students pointed out, this practice can leadto better understanding by the public and act as a leverageto governments and organizations to protect the environment.Social pressure could then demand thorough environmentalstudies for large constructions that could jeopardize the ecosys-tem. Although this perspective seems ideal, younger studentsrecognized the danger of depreciation, i.e. at the beginning,users may become sensitive about the environment and act toprotect it, but after some months they could see their actions invain, realizing that their personal impact is very small. Futureresearch needs to consider how to avoid this boomerang effect.

It is somewhat contradictory that both user groups askedfor personalization and notifications, but they did not makeextensive use of the urban mashups. Possible explanations arethat the number of supported services was limited and that themashup feature should be friendlier with a simpler design.

Trustworthiness and accuracy of measurements are impor-tant matters, which become more complex when citizenscan contribute with their own services in a participatory-based scheme. In this case, reputation-based systems couldbe employed for raising trust. UrbanRadar would then utilizeonly reliable services for informing the users.

This case study helped us to identify eleven design princi-ples, which the authors consider important for future mobileapplications that deal with remote sensing of the physical andurban environment. These patterns are the following:

1) Personalization and user profiling. The applicationmust be able to understand the preferences and needsof the user, and inform him only about services of in-terest. More advanced, the application could record theactivities of the user (e.g. sports, work), or his require-ments (safety, health) and provide to him meaningfulinformation about relevant environmental aspects.

7http://www.google.com/glass/start/what-it-does/

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2) Notifications and alerting. The user shall not needto interact with the application all the time. The ap-plication must monitor the environment for dangeroussituations or abnormalities and inform the user onlywhen suspecting or encountering any of these situations.

3) Recommendations of the mobile application in caseof dangerous situations such as earthquakes, fires orstorms. The application should suggest to the user howto react and the right actions to perform.

4) Forecasting and predictions about future environmentalevents and warnings to the user.

5) Accuracy and reliability of measurements.6) Meaningful data. Users prefer to associate measure-

ments with their direct impact on the environment,including -if possible- ways to improve the situation.

7) Easy rule creation. Users must be able to develop theirown rules very easily, in just a few clicks, combiningenvironmental services together and producing moreadvanced events. They shall be able to specify onlyeasy-to-understand values such as low/average/high.Moreover, more advanced users should have the optionof configuring their rules more precisely, e.g. to defineranges of measurements or logical operators.

8) Visualizations such as map coloring and historical datagraphs can be provided for helping the users to perceiveambient conditions such as air quality.

9) Comparative feedback and normative social influencecould raise the awareness of users and increase theirunderstanding, through comparisons with the conditionsat the locations where friends and relatives live. Com-petitions between areas would be promising as well.

10) Locating the source of the problem. In case ofdegradation of the physical environment, users shouldbe able to ask from mobile applications to identify tothem what the cause of the pollution is, or at least tolocate areas in which this degradation occurs.

11) Eco-visualizations8 such as bracelets, blended with theeveryday lives of people, could be used for informingthe users unobtrusively for environmental conditions.

VII. CONCLUSION AND FUTURE WORK

This paper described a case study on the impact of remotesensing in the everyday lives of mobile users in urban en-vironments. By means of mini focus groups, the influence,usefulness and potential of this approach was discussed. Basedon user feedback, eleven design principles were identified,which could be considered in future relevant initiatives.

Our case study is apparently limited, applied only in acampus environment with a small number of participants. Inorder to generalize and promote deeper discussion, we need toconduct experiments in various environments, with more usersand a longer experimental period. For future work, we plan toperform larger studies, integrating the aforementioned designpatterns to UrbanRadar, involving hundreds of sensor devicesand participants, extending the study for several months. Our

8Eco-visualizations could interact with mobile remote sensing applicationsto update their content in real-time.

focus would be to better monitor and analyze the influence ofremote sensing in the lifestyles of citizens.

We believe that mobile remote sensing can contribute in theactive involvement of citizens with their urban landscape. Byinteracting with their local environment, people would becomemore aware about their area, ensuring a higher quality of life,health and safety. The concept of UrbanRadar can constitutea driver towards the vision of a real-time digital city.

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