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SENSEABLE CITY LAB

Re-Imagining Streetlight Infrastructure as a Digital UrbanPlatformRicardo Álvareza, Fábio Duartea,b, Alaa AlRadwana, Michelle Sita and Carlo Rattia

aSenseable City Lab, Massachusetts Institute of Technology, Cambridge, USA; bPontifícia UniversidadeCatólica do Paraná, Curitiba, Brazil

ABSTRACTUrban infrastructures have traditionally been mono-functional:water, sewage, and electricity are notable examples. Embeddedwith digital technologies, urban infrastructures have the potentialto communicate with one another and become multi-functionalplatforms that integrate data gathering and actuation cycles. Inthis paper, we focus on public lighting infrastructures. Despite thetechnological development of lights, including LED technology,streetlights have been primarily treated as a mono-functionalinfrastructure. Based on case studies, we discuss the potential ofreimagining streetlight infrastructure, and advance some initialproposals that focus on sensing and actuation cycles, which couldtransform this pervasive infrastructure into a digital urban platform.

KEYWORDSStreetlight; smart-lighting;urban infrastructure; digitaltechnologies; internet ofthings

Introduction: Large-Scale Infrastructure Systems—From Mono-toMulti-Functionality

Urban infrastructures have been a dominant component of the physical form of cities.More recently, technological developments have allowed a wide array of cheap miniatur-ized electronic sensors and control systems to be inserted into the urban fabric whilebecoming interconnected to large operational and information systems through telecom-munication networks. In the process, virtual and physical urban features have merged,forming spaces that are made simultaneously of both atoms and bits (Mitchell, 1996).Although infrastructures are still at the core of the urban space, they have acquired aninformational level that do not impose specific physical forms, but actually have infiltratedinto the urban fabric (Duarte and Firmino, 2009). Gordon Pask, a leader in cyberneticswho experimented with interactive environments in the 1960s, advanced how the inte-gration of sensors, data, actuators, and feedback-oriented networks would have profoundinfluences on society in general, and in the urban environment in particular, arguing thatarchitects are “first and foremost system designers” (Pask, 1969: 494).

However, even with this gradual process in place, cities have struggled to create digitallymediated environments that foster human-centered experiences. For cities, integratingthese digital platforms in their environments present a series of relevant challenges likedemonstrating immediate benefits to the public in order to justify the required

© 2017 The Society of Urban Technology

CONTACT Fábio Duarte [email protected]; [email protected] Senseable City Lab, Massachusetts Instituteof Technology, MIT 9-209, 77 Massachusetts Ave., Cambridge, MA 02139, USA

JOURNAL OF URBAN TECHNOLOGY, 2017http://dx.doi.org/10.1080/10630732.2017.1285084

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investments. Large-scale infrastructure systems have frequently been characterized as“natural monopolies.” This means that they require a large initial capital investmentand have high operational costs that gradually decrease in the long run due to the decreaseof unit costs as the market scales up (Kunneke, 1999). If the long-term market is guaran-teed, this pattern of behavior is usually of interest for a company to invest in, where pol-itical and economic decisions aimed at securing this have been common in history(DiLorenzo, 1996). To this degree, it is easier to sell new technologies simply as enhancersof existing functionalities and constrain the development of any additional services thatmight leverage these platforms but involve additional investments. Cities often integratesolutions on a case-by-case basis without having a coherent architecture strategy. Thisnegates the greater possibility of strategizing the value of the data in the developmentof services that leverage existing infrastructure. These dynamics create a relevant seriesof constraints that give little room to city officials to imagine and experiment with newforms of urban spaces and services. Still, cities around the world are rethinking ways ofprojecting the value of existing infrastructure forward by merging the physical anddigital into a coherent whole, creating new urban experiences in the process.

The main goal of this paper is to advance potential multi-functional uses for streetlightsto take advantage of five assets: guaranteed energy supply, seamless blend into the urbanlandscape, verticality of the lamppost form, their ubiquitous presence in cities, and evendistribution throughout urban areas. We begin the paper by presenting how lighting com-panies and cities are leveraging light-emitting diodes (LEDs) to find novel uses for street-lights. Then, we propose a conceptual framework to transform this mono-functionalinfrastructure into a multifunctional digital urban platform. Within this framework, wediscuss four cases in the United States, which are exemplars of the different stages ofthis process. Finally, we advance a few ideas on the possible uses of leveraging streetlightinfrastructure as a multifunctional digital urban platform.

Re-Imagining a Ubiquitous and Mono-Functional Infrastructure

A major innovation in the lighting industry has been the introduction of light-emittingdiodes technology. LEDs were invented decades ago, but only recently have become acommercially attractive technology. Recently, LED luminaires have rapidly been intro-duced in urban areas. Valentová et al. (2015) surveyed 106 pilot LED cases in 17 Europeancountries, mostly focused on retrofitting outdoor lighting for areas with low volumes oftraffic. The authors found an average energy savings of 59 percent, in combining LEDtechnology and other lighting efficiency measures. According to the Department ofEnergy (US Department of Energy), by 2030 the adoption of LEDs in the United Stateswill save the country approximately $30 billion dollars a year. It will also reduce gas emis-sions by the equivalent of 40 million cars, and decrease the dependency on fossil-fueledenergy plants. In Mexico, Garcia et al. (2014) showed that upgrading street lighting toLEDs in Ciudad Juarez would result in 64 percent of energy savings. Beyond energy effi-ciency, LED based streetlights also have a key benefit: they are digital, and hence can beconnected to larger information systems. This is a fundamental change in which street-lights that once transformed electrons into photons, now simultaneously createinformation.

2 R. ÁLVAREZ ET AL.

Triggered by LEDs, cities and lighting industries are realizing that the mono-function-ality of streetlight infrastructure is limited in perspective. The Danish Outdoor LightingLab (Danish Outdoor Lighting Lab) is an urban testbed for several lighting companiesto deploy their lighting solutions, including the integration of different technologiesthrough streetlight infrastructure. Cities deploying LED lights are basing their decisionson two arguments: economic and sustainability. LEDs consume less energy. Therefore,they have lower maintenance costs, and are less dependent on fossil fuels (in theUnited States and Europe) and nuclear plants (in parts of Europe). While energysavings is a dominant motivation for intelligent infrastructures, the emergence of smartgrids and their connection to streetlights presents yet other significant potential of inter-connected networks, such as expanding wideband digital communications capabilities inthe urban space. In this context, technological structures could “transform the city to acontext-aware, smart, energy-efficient environment capable of effectively responding toemergent conditions and functioning as an informatics interface” (Ratti, Nabian, 2011:25).

A few cities have been exploring the deployment of sensors on streetlights to collecturban data, ranging from pollutant emissions to traffic counting; fewer have been usingstreetlights and information technologies to create Internet meshes or to deploy surveil-lance systems. Sarah Murray (2015) provides the example of Christchurch, in NewZealand, which has been deploying multiple sensors ranging from water quality totraffic flows, and highlights the potential of using lampposts. As Mayo Nissen (2014)writes, “These unseen sensors are the instantiations of large invisible systems that havea very real impact on the lived urban experience.”

Global lighting companies such as Philips, General Electric, and Osram have beenlaunching smart lighting solutions that go beyond controlling LED luminaries, includingembedding sensors that can detect phenomena in the urban environment, such as camerasand environmental sensors, in lampposts. But rather than moving forward with clear strat-egies, they produce tentative approaches with undefined and broad goals—as Will Rhodes,a market researcher at IHS Technology Consultants said in Fortune Magazine, “Their tra-ditional business is falling faster than their LED business is taking off” (Higginbotham,2015). This is likely because LEDs outlast the shorter replacement cycles of traditionallight bulbs and disrupt additional revenues companies would make from them. Thisfast pace in technological shift might explain the scarcity of scholarly assessments oranalytical frameworks to foster the exploration of the possibilities offered by the ubiquity,discretion, and even distribution of streetlights in order to create a comprehensive urbanknowledge platform. A rare and partial example is a paper by Erlandson and Psenka(2014), which presents initiatives ranging from streetlights that harvest solar power anddistribute the energy through the grid, to the provision of customized music programs,alert signs, street-light-on-demand, and push-to-talk systems using lampposts andsmart grids, done by some of these companies as well as other smaller players such as Illu-minating Systems from Michigan.

The lack of coordination between different sensors makes it difficult to automaticallyassemble, analyze, and actuate on diverse data in efficient ways (Resch et al., 2009). Thenext section discusses two key aspects on how the incorporation of digital technologiesmight transform streetlight infrastructure into a digital urban platform: combiningsensing and actuating technologies. We then discuss four cities in the United States,

JOURNAL OF URBAN TECHNOLOGY 3

which have been leveraging streetlight infrastructure by deploying sensors, and which areat different levels of development.

Conceptual Framework: Creating an Urban Digital Platform

As with almost every innovative technological breakthrough, structural changes comeslowly, following more tentative steps rather than an overarching plan. This isespecially true when it involves large, mono-functional, and long-lasting infrastructuressuch as streetlights that are grounded in a century-long economic and technologicalmodel.

LEDs have affected business models of public lighting. LED projects typically beginwith improving their core functionality: providing better illumination, using less energy,and reducing capital and operational costs. Moving beyond this, to further enhance light-ing operations, some cities are equipping lampposts with wireless connection capabilitiesto meter energy consumption and control each luminaire individually. With this pervasivepublic Internet mesh, some cities are also leveraging existing lighting infrastructure bymounting surveillance cameras on lampposts, or attaching microphones with micro-processing boards to streetlights that send an alert with its location to law enforcementwhen they detect unusual sounds such as a gunshot. In these cases, streetlights are usedto articulate different sensing technologies and urban services, a process that involvesdifferent stakeholders within the public sector.

Coupled with these capabilities to connect to communication and information technol-ogies, we further see the potential for a direct interplay between streetlights, public infra-structure, and mobile and other personal devices to serve as extensions of actuation andinteractive cycles to the public. At the core of this idea are the interconnected networksof sensors, actuating elements, databases, and people interacting with each otherthrough these networks and transforming the relationships between people and urbansystems.

The data collected in some cities could not only be shared with the companies that ownthe streetlights and sensors but also with the public, opening up data streams to be used byanyone interested in developing applications for mobile or other personal devices. Theseinteractions or applications would enable the average citizens to fully utilize the data gath-ered by streetlights for their personal purposes, such as checking whether a school is safeafter an earthquake, or further interact with streetlights to customize urban experiences.The mesh of sensing technologies, opening data, and articulating static and mobile tech-nologies has the potential to create urban experiences while exploring actuation cycles andthe integration of sensing and actuating technologies as components of this multi-func-tional urban knowledge platform.

Sensing and actuating technologies are keystones for transforming streetlight infra-structure into an urban knowledge platform. A mesh of multipurpose sensing technologiesand communication networks can allow cities to collect and transmit an array of data inreal time, which might foster complex analyses of urban phenomena for posterior orimmediate action. But sensing without actuation is pointless. Lampposts might becomemore than a stand for sensors and become part of the responsive infrastructure, by inter-acting with other actuation technologies embedded in urban infrastructures, transpor-tation systems, and personal devices.


In the next section, we discuss four cities in the United States that represent differentphases in the evolutionary path of transforming a mono-functional urban system into amulti-functional one. These cities serve as an illustration, not a comprehensive panel ofthe dozens of initiatives around the world. We have not included cities that are simplyswitching to LEDs without adding other sensors, nor those that are not adding at leastone actuating cycle beyond controlling luminaires.

Case Studies

San Diego

In 2014, San Diego switched 3,000 high-pressure sodium (HPS) streetlights to LEDs in theGaslamp Quarter tourist district. In addition to switching to LEDs, San Diego is the firstcity in the United States to employ General Electric’s LightGrid technology, a web-enabledcentral management system that allows for remote operation and monitoring. The systemmeasures the energy consumption of each lamppost, detects necessary maintenance, andallows for independent control of each luminaire which will offer residents, businessowners, and visitors improved and energy-efficient lighting that will significantly trimthe city’s spending and maintenance needs (Current: Powered by GE a). Aside from anoperational impact, the system further benefits the environment by reducing uplightingand CO2 emissions (Current: Powered by GE b). Officials expect to save more than$250,000+ annually by consuming less energy and advancing lighting management,which can potentially be done at a singular unit level. The city can expect even moresavings when the system is moved toward a metered rate rather than a flat-rate tariff(Current: Powered by GE b).

In 2015, the city in partnership with General Electric signed an agreement to install 50lampposts embedded with a larger array of sensors and software platform that will help thecity with traffic and parking optimization, and environmental monitoring (Kellner, 2015).Currently, there is no publicly available documentation on the actual implementation,sensors to be used, or expected results of the deployment of GE’s Intelligent Cities tech-nology in San Diego.

Los Angeles

In 2013, Los Angeles began replacing 140,000 of its regular streetlight bulbs with LEDs.The city uses Philips’ CityTouch technology, a software designed to link all lightingassets in an infrastructure, and one that allows municipal officials to track energy con-sumption and remotely control each individual luminaire. The city has saved $8 milliona year since, and has improved lighting control in specific areas (Philips, 2016).

Although the initial phase of upgrading streetlights was strictly framed as a manage-ment project, the city intends to equip them with sensors to monitor air quality andnoise pollution. Streetlights will be embedded with GPS-based technology operatingover 4G LTE cellular networks, which will enhance open Wi-Fi coverage, inform theBureau of Street Lighting which lampposts require maintenance, and allow individualcontrol over each streetlight. This decision resulted from a partnership between Ericssonand Philips to combine Ericsson Zero Site technology and Philips SmartPole technology.


As mentioned by Ed Ebrahimian, the city’s Director of the Bureau of Street Lighting,“It’s basically our eyes and ears all over” quoted in (Heaton, 2015). In 2015, the citybegan installing 100 of these “smart streetlights” and plans to install 600 by the year2020 (LED Inside, 2015).

New York

New York has recently made multiple efforts to upgrade their streetlight infrastructure to asmart lighting infrastructure. In 2013, New York began replacing its existing 250,000 HPSstreetlights to LEDs, forecasting an annual savings of $6 million in energy consumptionand $8 million in maintenance. Two years later, New York partnered with General Electricto deploy smart streetlights that would include environmental sensors to measure airquality, microphones, cameras, and motion detectors. The New York Department ofTransportation believes these sensors will help manage pedestrian and vehicle flows;however, some concerns regarding privacy have been raised (Newman, 2015).

In 2015, General Electric installed a temporary streetlight prototype on East 22nd Streetthat interactedwith passing pedestrians. Although the demonstration used a hidden actor tointeract with pedestrians, the exhibit successfully demonstrated the potential of collectingdata from the city through sensors mounted on lampposts and displaying informationsuch as weather, traffic, and free parking in applicable ways to users through their smart-phones or other devices (Ebi, 2015). In the same year, General Electric partnered withSST, Inc. to install ShotSpotter technology in lampposts in New York—initially in sevenareas in the Bronx and ten in Brooklyn, covering a 15-square-mile area. ShotSpotter,which has been used in several cities across the country, pinpoints gunfire through soundtriangulation—the shot must be detected by microphones in three different lampposts,and the sound pattern is analyzed by technicians at SST headquarters. Once the likelihoodof the sound is estimated to be gunfire, the system sends the location to law enforcement,police stations, and police officers’ cellphones in near real time.

Chicago

Initiated in 2016, Chicago’s smart-streetlight project plans to deploy 150 sensing nodeswithin the boundaries of the Loop area in downtown Chicago, and deploy 200 nodesby the end of 2017 to create a larger sensor network—which the city envisions as a newkind of civic infrastructure (Crawford, 2014)—and cover a larger area for data collection.This initiative is called the Array of Things. It seeks to use a distributed streetlight infra-structure to deploy a range of sensors to collect real-time data on temperature, barometricpressure, light, vibration, carbon monoxide, nitrogen dioxide, sulfur dioxide, ozone,ambient sound intensity, pedestrian and vehicle traffic, and surface temperature. Inte-grated in a one-square-foot box, these sensors may bring smart lighting infrastructureto a higher level beyond managing LED luminaries remotely. Although the number ofrepurposed lampposts is not necessarily more than other cities which are deployingsmart streetlights, Chicago’s smart-streetlight project is arguably the most comprehensiveto date with a wider array of sensors and the intention to involve a larger variety of sta-keholders to explore the data to be gathered.


Researchers are planning to process some highly sensitive information, such as imagesgathered from the 5MP camera, on-board within the sensor node in order to guarantee thepublic’s privacy by extracting relevant information and sending the relevant metadata tocloud servers (Urban Center for Computation and Data, 2016). The data will be madepublic on different open source platforms, which will allow the public—includingresearchers, developers, and civic groups—to use the data to better understand specificfeatures of the city and create applications.

According to the plans made available by the city, the project does not have anyplanned actuation cycles so far. The system further minimally utilizes mobile devicesfor data collection purposes. For instance, to detect pedestrian density, the system is pro-jected to use Bluetooth to ping personal mobile devices to count pedestrians in certainareas. However, potential actuations may be developed in the future from applicationsdeveloped by the public.

The Array of Things is led by researchers from the Urban Center for Computation andData of the Computation Institute, a research initiative of the Computation Institute at theUniversity of Chicago and Argonne National Laboratory. The project has a multitude ofpartners, including the Department of Information and Technology as well as the Depart-ment of Transportation. The underlying software and hardware design was developed atArgonne National Laboratory and the sensor node enclosure has been designed by stu-dents from the Art Institute of Chicago.

Analysis of Case Studies

The cities mentioned in this paper have different levels of complexity and geographicrange. In some of the cases, cities have only added another service to the lamppost,whereas others have made a serious attempt to create a mesh of sensors to gather and dis-tribute data of the urban environment. In some cases, data gathering and management aredone in closed systems, mostly for lighting management, and in others the data is open tothe public. Stakeholders also vary from projects driven by lighting and information tech-nology companies to others led by municipal governments.

Including all those described here, cities recognize that sensing technologies will soonbe embedded in streetlights. However, the ad-hoc mentality of encapsulated services placesa barrier for their full maximization. As a consequence of this, the data being captured bythe sensors are being used for singular purposes, instead of being recombined for a widevariety of uses. To this extent, cities are still struggling to maximize the full potential of thetransformation from analog to digital platforms in public lighting systems. Many citieshave sent out press releases stating that they will deploy environmental sensors on lamp-posts; however, many of them have largely focused on implementing cameras and micro-phones primarily for security uses. Currently, cities have released very littledocumentation on their specific plans to actuate on the gathered sensor data. Manycities have broadly declared their intentions to implement systems to help drivers findstreet parking or interfaces to show the weather, but these ideas are frequently mentionedwithout specific details about the sensors, technologies, or public investments that arenecessary to implement such projects. A more comprehensive and creative combinationof the use of multi-data streams along with a wider variety of actuation cycles will benecessary to leverage sensor technologies, maximize the value of streetlights as a new


type of urban infrastructure, and justify the investments required for theirimplementation.

Simultaneously, other types of urban infrastructure systems as well as personal deviceshave been largely underutilized and forgotten in the incorporation of this infrastructure.The few interactions between lampposts and mobile devices that are mentioned in thematerials researched simply cover some basic interactions such as providing wireless con-nectivity or sending some information to mobile devices. These interactions are oftenbroadly stated without any specificities or a high degree of innovation. There is a clearopportunity to create dynamic interactions between these technologies and services,and fully draw on the fundamental ideas of the Internet of Things in which digitaldevices are interconnected and communicate with each other with or without humanmediations for a wide variety of effects.

Envisioning Streetlights as a Networked Urban Digital Platform

In order to leverage the potential of streetlights as a networked urban digital platform, wepropose a taxonomy of use cases based on sensing technologies, datasets, and actuations(See Figure 1). In some cases, the data gathered from a single sensor can be analyzed andused to design a complete actuation cycle. For example, ShotSpotter is a clear applicationthat extracts value from sound data through machine learning processes, hence justifyingan investment in microphone technology. However, ad-hoc sensor implementations ofsensors only hold value depending on the specific targeted use. Our proposal presents aframework where we seek to extract the greatest amount of value from sensor technologiesand their streams of data. This is done through two processes: one is by extractingadditional value through the continuous reinterpretation of available data and the otheris by finding new creative uses through a combination of multiple data streams.

Figure 1. Taxonomy of sensing/actuation cycles


Collected data have different meanings and value for different contexts and uses; dataalso hold additional value when analyzed at different temporal and spatial scales. Forexample, visual data collected from an image sensor can be used to help identify availableparking spots in cities, by detecting the presence (or lack) of an automobile in a designatedarea. While this data can be relayed to users in real time, the same data can also be used foroptimizing the availability of parking conditions in a city though a longitudinal analysis ofthe full visual dataset obtained from all the cameras deployed in the urban environment.However, the same data can be mined for other uses, such as monitoring traffic conditions,the frequency of urban services such as transportation or waste collection, or the study ofhuman behavior in public or retail spaces. It is possible to develop multiple uses fromdifferent interpretations of the same data. Figure 2 shows how a single visual datasetcan be used for multiple uses and applications.

Taking the previous example of on-street parking, we can show how a single sensor canbe leveraged to create a solution when integrated with wireless communication platformsand smartphone technologies. Car parking availability in cities is a recurrent and criticalconcern. Up to 30 percent of traffic in congested downtown areas is caused by driverslooking for parking spots (Shoup, 2011). This has severe consequences in terms of pol-lution and economic inefficiencies in cities. Additionally, given that parking serves adynamic need, the lack of real-time knowledge regarding availability of parking spacesconstitutes a potential financial loss for cities given that they cannot operate dynamicpricing models that would allow them to maximize the value of the real estate allocatedfor street parking. As such, in recent years many cities have implemented “smartparking” solutions that often use additional sensors placed on parking meters or on theground to detect availability (Nawaz et al., 2013). Combining cameras and computervision techniques, it is possible to detect not only real-time availability of parkingspaces, but also measure the size of the available space. This information is relevantbecause different car models can have different space requirements for parking. Theextracted information could then be matched to a database of vehicle models and usedto inform a driver through their smartphones or car dashboards if an available spot willfit her car. This additional information becomes a clear competitive advantage towardsother available solutions. This dynamic model combining sensing and communication

Figure 2. Single sensor, multi uses


technologies (See Figure 3) would decrease the time consumed by drivers trying to findon-street parking spaces for their specific needs.

This logic can be applied to various types of sensors. Taking sound data as an example,a single dataset might be mined for specific sound patterns, and signatures. These could bematched with particular interpretations and uses like detecting gunshots or car accidents;mapping sound pollution levels throughout a city, or performing vehicle density flows andclassification for transportation planning. Motion sensors such as inertial measurementunits can simultaneously be used for infrastructure as well as seismic movements moni-toring, and so on. The key is in the interpretation of the data and the creative ways of creat-ing cycles of interaction and actuation.

Beyond leveraging multiple uses for a single sensor, there is the possibility of leveragingtwo or more sensing outputs toward higher-value information. This might be the case ofsound sensors and air quality sensors for example. Microphones can be used to detect bothparticular sound frequencies as well as sound pressure levels. To this extent, machinelearning algorithms may be used to extract vehicle count and classification from frequencyvariations and specific sound signatures. This data can be combined with air quality dataextracted from sensors that can monitor a variety of pollutants such as NOx, CO, and airparticulate matter to correlate the vehicle count and classification to pollution levels insitu. Isolated, each sensor has particular functions, but by finding correlations betweensound and air quality we can aggregate value to the sensing package. This data couldthen be used for several purposes such as developing smarter actuation cycles in net-worked traffic lights or develop environmentally friendly transportation policy.

Figure 3. Detection and communication cycles of automated parking detection system


Multiple sensing and actuating cycles integrated with streetlights could be developed foremergency scenarios. Public safety and security are areas of major concern in urban areas.Urban safety depends on timely detection and responses to hazardous incidents. Emergen-cies, ranging from localized car accidents to natural disasters, gas leakages, crime events, oreven potential terrorist attacks can seriously disrupt the urban dynamic and have lastingrepercussions in regard to human lives if they are not handled appropriately and in atimely manner. Given the density of streetlights, sensors such as digital cameras, micro-phones, and gas and motion detectors can be mounted on them in order to detect a widevariety of incidents. While digital technologies such as “ShotSpotter” that help detect particu-lar types of incidents have been improving and are becoming “smarter,” emergencyresponses have largely remained unchanged: law enforcement and rescue teams are sentto the location of the incident to guide people’s behavior, assist victims, and control the situ-ation. However, there is a delay in communicating this information to people in the vicinityof the emergency who may be in danger and may suffer preventable injuries or deaths.

The ubiquity of existing lighting infrastructure could be used to not only automate thedetection of public safety incident hazards, but moreover to integrate actuation cycles byusing lampposts as information systems in emergency response cycles for people andinfrastructure. Lighting infrastructure can be used to respond faster to emergency situ-ations, help public authorities control the situation, and potentially save lives. Forexample, immediately after a car accident occurs, lights mounted on lampposts canturn orange and blink, alerting drivers to slow down and prevent pileups. In anotherexample, gas sensors mounted on lampposts sense a noxious gas leakage. Sensorswould send an alert to the public authorities who would start monitoring the areathrough cameras, as well as sending messages to 911, already specifying the event. If anincident has been confirmed, Wi-Fi and radio transmitters mounted on lampposts

Figure 4. Emergency events: sensing and actuation cycle


would automatically send amber alerts to the cellphones of those in the area; or, if it is anincident with a larger impact (such as a bomb), cellphone towers would send the alerts toeveryone within the coverage area. The lampposts themselves can work as actuators (SeeFigure 4). In both cases (gas leaks and bombings) the area needs to be evacuated throughsafe routes in an orderly way. Through light or sound, lampposts can help direct people tothe evacuation routes, as well as alert people to not approach the incident area. Althoughthis list is not comprehensive, it is possible to match different types of incidents withdifferent types of safety responses, creating a sensing and actuating taxonomy in casesof safety risk incidents in urban areas.

By maximizing the potential interpretations of data gathered by sensors, and pairingthem with actuating technologies embedded within the urban environment and personaldevices, we can generate profound changes in core urban infrastructures, migrating from asingle function perspective that restricts their potential value to a multi functionalapproach that leverages technologies to multiply potential value to cities and citizens.

Conclusion: Streetlights as an Urban Knowledge Platform

Fostered by LED and network technologies, cities are beginning to invest in turning street-lights into an infrastructure platform capable of performing multiple functions simul-taneously. Beyond the simple conversion of HPS streetlights to LEDs aimed at savingmoney by lowering energy consumption and enhancing lighting management at an indi-vidual level, cities are deploying sensors to gather varied data from cities and providingadditional public services. These services range from providing public access points tothe Internet to collecting data about weather and traffic; from detecting gunshots to locat-ing available parking spaces.

And yet, even in cases where technological layers are added, there still is a lack ofintegrated architecture behind these efforts. Our research suggests that this is in partdue to the ad-hoc solutions approach behind the installation of each sensor. When aresponsive system is in place, it commonly works in a closed loop: data are collected,analyzed, and trigger standard responses only to particular problems; this places artifi-cial restrictions on the potential of the digital platforms used. In this paper, we pre-sented some efforts from cities that are implementing promising initiatives, but stillare short of achieving full interoperability that turns streetlights into a comprehensivedigital urban platform.

In the last section of this paper we have presented a conceptual framework that pro-poses a continuous reinterpretation of the collected data from sensors, along with a com-binatorial logic of multiple sensors and actuator technologies that could workinteroperably to provide new services. Finally, through an exercise in speculative design,we have presented some potential solutions to best exemplify the recommendations ofour framework in transforming a mono-functional infrastructure into a multi-functionalone that provides a more comprehensive and systematic understanding of urban phenom-ena and creates new forms of experiencing cities.

Disclosure Statement

No potential conflict of interest was reported by the authors.


Acknowledgements

The authors would like to thank Allianz, UBER, Fondation OCP, Liberty Mutual, Ericsson, SaudiTelecom, American Air Liquide, Volkswagen Group America, Philips, Austrian Institute of Tech-nology, Fraunhofer Institute, Kuwait-MIT Center for Natural Resources, SMART—Singapore MITAlliance for Research and Technology, AMS Institute Amsterdam, Victoria State Government, andall the members of the MIT Senseable City Lab Consortium for supporting this research.

Notes on Contributors

Ricardo Álvarez is a researcher and PhD candidate with the Senseable City Lab of MassachusettsInstitute of Technology.

Fábio Duarte is a scholar and research lead at the Senseable City Lab of Massachusetts Institute ofTechnology and a professor at Pontifícia Universidade Católica do Paraná, Brazil.

Alaa AlRadwan is a researcher at the Senseable City Lab of Massachusetts Institute of Technology.

Michelle Sit, is a researcher at the Senseable City Lab of Massachusetts Institute of Technology.

Carlo Ratti is a professor of the practice and director of the Senseable City Lab of MassachusettsInstitute of Technology.

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