Smart cities began as marketing, but local civil servants are quietly making them real – Technical.ly

Report on the Evolution and Sustainable Implementation of Smart City Initiatives

Executive Summary

The concept of the “smart city” has evolved from a corporate marketing term into a substantive framework for improving urban governance and resident well-being. This report analyzes this evolution, placing significant emphasis on its alignment with the United Nations Sustainable Development Goals (SDGs). True progress in smart city development is contingent not on the acquisition of novel technologies, but on strategic coordination, sustained political commitment, and a focus on delivering tangible benefits that advance urban sustainability, equity, and resilience. The integration of technologies like Artificial Intelligence (AI) presents opportunities to accelerate progress toward the SDGs, but requires transparent and accountable governance to mitigate risks such as increased surveillance and inequality.

The Smart City Paradigm: From Marketing to Sustainable Urban Development

Origins and Evolution

The term “smart city” emerged in the late 1990s, alongside the “Internet of Things” (IoT), largely driven by corporate campaigns to sell technological infrastructure to municipal governments. The initial vision, however, has matured into a more practical application of hardware and data science to enhance the efficiency and effectiveness of urban systems. This shift aligns directly with SDG 11 (Sustainable Cities and Communities), which calls for making cities inclusive, safe, resilient, and sustainable.

Core Tenets of Modern Smart Cities

• Data-Informed Governance: Utilizing data to improve municipal functions, from online permitting to infrastructure monitoring, supports SDG 16 (Peace, Justice, and Strong Institutions) by creating more effective and accountable institutions.
• Focus on Resident Outcomes: The primary goal is to achieve better outcomes for citizens, such as improved public safety and more efficient services, rather than deploying technology for its own sake.
• Integration of Systems: The concept centers on linking complex urban systems—such as transport, utilities, and governance—through digital feedback loops to create a cohesive and responsive urban environment, contributing to SDG 9 (Industry, Innovation, and Infrastructure).

Technological Applications for Advancing the Sustainable Development Goals

The Role of AI and Data in Urban Management

The current wave of smart city innovation is characterized by the integration of AI. This technology is being embedded across core government functions to enhance planning and service delivery. These applications offer direct pathways to achieving specific SDG targets.

• Infrastructure and Environmental Management: AI-driven infrastructure planning and air pollution tracking systems, as seen in recent initiatives, directly support SDG 11.6 (reduce the adverse per capita environmental impact of cities) and SDG 3 (Good Health and Well-being).
• Mobility and Public Safety: The use of data and sensors to manage urban mobility and enhance public safety is a cornerstone of smart city projects.

Case Studies in SDG-Aligned Innovation

1. Los Angeles’ Mobility Data Specification (MDS): By creating an open-source standard to regulate shared mobility services (scooters, bikes), the city enhances its ability to manage public transport systems, directly contributing to SDG 11.2 (provide access to safe, affordable, accessible and sustainable transport systems).
2. Philadelphia’s Automated Speed Enforcement: A pilot program that reduced speeding by over 90% and cut serious crashes demonstrates a data-backed approach to improving road safety, aligning with SDG 3.6 (halve the number of global deaths and injuries from road traffic accidents).
3. Seattle’s Open Mobility Foundation Alliance: A pilot linking 911 dispatch data to robotaxis to prevent them from blocking first responders is an innovative use of technology to improve emergency services and public safety, supporting both SDG 11 and SDG 3.
4. Open Data Platforms: Initiatives like OpenDataPhilly foster transparency and accountability, which are central tenets of SDG 16.6 (develop effective, accountable and transparent institutions at all levels).

Challenges and Strategic Recommendations for Sustainable Implementation

Addressing Risks to Ensure Inclusive Growth

The deployment of smart technologies is not without risks. International bodies like the OECD caution that without proper oversight, these tools can deepen inequities and enable surveillance, undermining progress toward SDG 10 (Reduced Inequalities) and SDG 16. Key challenges include:

• The risk of overwhelming policymakers with raw data without clear strategies for its use.
• The potential for AI-driven systems to reinforce existing biases if not implemented with a focus on equity.
• The need for robust public oversight to ensure technology serves citizens and builds trust.

A Framework for Future Development

The success of smart city initiatives depends less on the technology itself and more on the strategic framework governing its use. The focus must remain at the state and local levels, where service delivery occurs and meaningful experiments can be scaled.

Key Recommendations

• Prioritize Coordination and Political Support: Sustained political commitment and inter-departmental coordination are more critical than acquiring new tools. This aligns with SDG 17 (Partnerships for the Goals).
• Embed Transparency and Accountability: Governments must pair technological experimentation with public oversight and clear governance strategies to maintain public trust and ensure ethical implementation.
• Center the Resident Experience: The ultimate measure of success is whether residents experience tangible benefits from digital systems, ensuring that innovation directly contributes to the quality of urban life as envisioned in SDG 11.

Analysis of Sustainable Development Goals in the Article

1. Which SDGs are addressed or connected to the issues highlighted in the article?

1. SDG 3: Good Health and Well-being
   • The article discusses public health and safety improvements through smart city technology. Specifically, it mentions the use of automated speed enforcement cameras in Philadelphia to reduce traffic accidents, which directly relates to promoting well-being and safety for citizens.
2. SDG 9: Industry, Innovation and Infrastructure
   • The core theme of the article is the use of technology, data science, and AI to build and manage urban infrastructure. It mentions “sensors monitoring infrastructure,” using AI for “infrastructure planning,” and the evolution of smart cities through new hardware and software, all of which fall under the goal of building resilient infrastructure and fostering innovation.
3. SDG 10: Reduced Inequalities
   • The article raises concerns that smart city technologies, if not implemented carefully, can “deepen inequities or enable surveillance.” This connects to SDG 10 by highlighting the need to ensure that technological advancements in cities do not reinforce existing social or economic disparities and are inclusive for all residents.
4. SDG 11: Sustainable Cities and Communities
   • This is the most central SDG in the article. The entire concept of “smart cities” is about making urban spaces more efficient, sustainable, and livable. The article provides examples related to urban mobility (regulating scooters and bikes), environmental monitoring (“air pollution tracking system”), public safety (rerouting robotaxis around emergencies), and improving municipal services (“online permitting,” “garbage collection”), all of which are key components of creating sustainable cities.
5. SDG 16: Peace, Justice and Strong Institutions
   • The article emphasizes “data-informed governance,” “efficiency in humdrum functions,” and the need for “transparency and public oversight.” It discusses how technology can improve citizen services and make government operations more effective and accountable. The caution against unchecked surveillance also relates to protecting fundamental freedoms, a key aspect of this goal.

2. What specific targets under those SDGs can be identified based on the article’s content?

1. Under SDG 3: Good Health and Well-being
   • Target 3.6: By 2020, halve the number of global deaths and injuries from road traffic accidents. The article’s example of Philadelphia’s speed camera program, which “cut serious crashes,” directly addresses this target by using technology to improve road safety.
2. Under SDG 9: Industry, Innovation and Infrastructure
   • Target 9.1: Develop quality, reliable, sustainable and resilient infrastructure. The discussion of using “sensors monitoring infrastructure” and AI for “infrastructure planning” aligns with this target of building and maintaining resilient urban systems.
3. Under SDG 10: Reduced Inequalities
   • Target 10.3: Ensure equal opportunity and reduce inequalities of outcome, including by eliminating discriminatory laws, policies and practices and promoting appropriate legislation, policies and action in this regard. The article’s warning that AI can “deepen inequities” implies the need to work towards this target by ensuring smart city solutions are designed and governed to be fair and accessible to all.
4. Under SDG 11: Sustainable Cities and Communities
   • Target 11.2: By 2030, provide access to safe, affordable, accessible and sustainable transport systems for all. The mention of Los Angeles’s Mobility Data Specification for regulating “scooters, bikes and potentially driverless vehicles” is a direct effort to manage and integrate new forms of urban transport sustainably.
   • Target 11.6: By 2030, reduce the adverse per capita environmental impact of cities, including by paying special attention to air quality and municipal and other waste management. The reference to a Brazilian city’s “air pollution tracking system” and Pittsburgh’s use of data to solve a “flaw in garbage collection” are concrete examples related to this target.
5. Under SDG 16: Peace, Justice and Strong Institutions
   • Target 16.6: Develop effective, accountable and transparent institutions at all levels. The article’s focus on “data-informed governance,” “transparency,” “public oversight,” and examples like “Boston’s 2015 CityScore” which aggregated performance metrics, all point to efforts to make municipal governments more effective and accountable.
   • Target 16.10: Ensure public access to information and protect fundamental freedoms. The mention of the OpenDataPhilly platform as “part of a national movement” for data releases directly supports public access to information. The caution against “surveillance” underscores the need to protect freedoms while implementing new technologies.

3. Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

1. For Target 3.6 (Road Safety):
   • The article explicitly mentions metrics from a pilot program: a reduction in speeding by “more than 90%” and a cut in “serious crashes.” These serve as direct indicators of progress.
     • Indicator: Percentage reduction in speeding violations.
     • Indicator: Number of serious or fatal traffic crashes.
2. For Target 11.6 (Air Quality):
   • The mention of an “air pollution tracking system” implies the collection of specific environmental data.
     • Indicator: Real-time data on urban air pollutant levels (e.g., fine particulate matter).
3. For Target 16.6 (Effective Institutions):
   • The article provides a concrete example of a measurement tool: “Boston’s 2015 CityScore, which aggregated dozens of performance metrics into one public number.”
     • Indicator: A composite index score (like CityScore) measuring the performance of various municipal services.
     • Indicator: Number of publicly available government datasets, as exemplified by the OpenDataPhilly platform.

4. Table of SDGs, Targets, and Indicators

Source: technical.ly