IoT-Enabled Smart Sustainable Cities: Challenges and Approaches
Abstract
:1. Introduction
2. Overview on a Smart Sustainable City
- share experiences, information, and projects, as well as responsibilities, among citizens, stakeholders and other institutions, for all the decisions that will affect the life of people in the upcoming years;
- strengthen the identity of the city as a capital city for well-known aspects (e.g., good food, culture, and music), and make the city more attractive for its citizens, tourists, and businesses; and
- focus on values in terms of ethics, social responsibility, and quality of services for people and companies.
- Strategic Environmental Assessment Plan (SEAP), targeting a reduction in CO emissions of a certain percentage, thus improving the global environmental conditions of the municipality.
- Sustainable Urban Mobility Plan (SUMP), aiming at
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- reducing private cars’ usage and allowing people to move in a more efficient, sustainable, and safe way;
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- re-designing the public transport network to cope with actual user expectations in terms of efficiency, quality and fast access to information;
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- developing inter-modality and interconnection with different urban transfer systems (e.g., bike and car sharing, electric mobility, car pooling);
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- improving environmental quality, by reducing noise and air pollution, and recovering urban spaces; and
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- reducing transport costs, energy consumption, and waste of resources.
- Sustainable Energy and Climate Action Plan (SECAP), aiming at (i) mitigating the environmental problems through decarbonization process, (ii) adapting to climate changes, and (iii) increasing energy efficiency for a secure and sustainable energy management.
2.1. Connectivity Infrastructure
- Low-Power Wide-Area Networks (LPWANs): This kind of network is especially designed to interconnect battery-powered devices with low bit rates over long ranges. Due to their low cost, wide coverage, and straightforward set-up, LPWANs are being deployed in different applications where a small quantity of data needs to be transmitted [10]. LPWANs work on both unlicensed and licensed frequency bands and include different standards (that can be open or proprietary), the most relevant ones are LTE-M [11], Narrowband IoT (NB-IoT) [12], and LoRa [13].
- 5G: Thanks to its advanced features, such as very low latency (less than 1 ms) and very high bandwidth (10 Gb/s), IoT is emerging as one of the primary use cases for 5G. Therefore, 5G can be considered as an enabling communication technology for smart cities, allowing more and more IoT devices to be connected to the Internet, regardless of their location and time, supporting applications such as smart traffic systems, public safety, security, and surveillance in the context of smart cities [14].
- Wireless Local Area Networks (WLANs) and short-range networks: Many use cases in smart cities require the deployment of “regional” (namely, covering a limited spatial area) and, in some cases, of “individual” networks (such as Personal Area Networks, PANs). In this context, the available communication technologies are extremely diverse, spanning from protocols based on IEEE 802.15 to Bluetooth and Bluetooth Low Energy (BLE) [15].
2.2. Sustainability Indicators
- explanatory indicators, corresponding to a well-defined set of indicators collected in order to evaluate the current state of the environmental dimension of sustainability in a city or urban area;
- pilot indicators, referring to indicators chosen specifically to assist policy-making; and
- performance assessment indicators, which are the most common ones and generally involve Key Performance Indicators (KPIs).
2.3. Smart City Challenges
3. Improving the Sustainability of a Smart City
3.1. An Illustrative Smart City: Parma
- economic solidity;
- sustainable mobility;
- environmental protection;
- social quality;
- governance;
- digital transformation.
- Smart transport and mobility;
- Smart energy, environment and smart grid, infrastructure;
- Smart society and people;
- Smart economy and innovation.
- Kick-off and Brainstorming World Café for Parma Futuro Smart (30 November 2017).
- Scenario—Vision Workshop (6 April 2018).
- From Scenarios to Roadmap Workshop (9 November 2018).
- Co-creation Workshop with the thematic groups (6 August 2020; 8 September 2020; 15 September 2020; 30 September 2020; 14 October 2020).
- Presentation of the Smart City Governance Plan (planned at the end of 2020).
- Urban regeneration of the existing city, through economic incentives and regulations that guide the market towards the improvement to extant buildings, avoiding any further soil sealing. The plan also identifies 15 strategic areas of urban regeneration.
- Reduction of land sealing, transforming of million m2 wide land initially classified to be used for building purposes into agricultural land and enhancing the agriculture and the environment through the transformation of up to 435 hectares of potentially building areas into agriculture land or natural parks, finally creating the Periurban Agricultural Park.
- Hydraulic and geological land safety, assuring the security of the territory and citizens through the Hydraulic Risk Management Plan and Seismic Micro-zoning Plan.
- Widespread service network, with several socialization places dedicated to culture and sports, to promote the quality of relationships between citizens, civic awareness, social inclusion, and perceived safety, particularly in suburbs.
- Facilitating the birth of centers of excellence, by multiplying the opportunities and maintaining high local production competitiveness and the strategic assets of Parma, such as trade fair, university, manufacturing, tourism, and agro-industry, also through city facilities well connected with transport infrastructure.
- Centralized control of traffic lights: The municipality sets up a light intersection management system in order to maintain a good coordination of the traffic lights in the urban area (algorithmic optimization) and regulate the duration of green lights depending on the intensity of the traffic.
- 3D RTE Parma Information Management: The Civil Protection department of the municipality of Parma has developed a geo-cartographic software for planning, managing emergencies, and for supporting decisions during critical phases. This software is linked to the Geographic Information System (GIS) of the municipality and uses a Global Positioning System (GPS) and a digital modeling. It contains different kinds of data, ranging from existing infrastructures to old people served by the municipal social services. The geo-cartographic core is the basis on which a whole series of services and functionalities can be implemented. The purpose is to share all the information already held by the municipality, that now stand in different departments. Moreover, this will ensure the full operation in terms of better knowledge, integration, and protection: this will improve the management and planning of the city and its resilience during critical events.
- Smart public lighting: Due to a refurbishment plan of the public lighting network of the city of Parma approved in December 2017, the urban lighting redevelopment plan involves a radical modernization of the city network, replacing the old systems with new LED-based ones. This allows a smart management and the installation of new surveillance and traffic control cameras and new sensors. Among a total of 36,613 lighting points, approximately 24,000 new LED lighting systems have been installed, with a linear network extension of 35 km. The project will end in 2035, with a total investment of 29 M€ (the contract has been already signed by the municipality).
- Traceability of bike sharing flows: The municipality runs a pilot project putting smart locks on 40 items of the bike sharing fleet, in order to monitor bike flows. In the future, a dedicated app will be developed for for the bike sharing system. At the moment, the city of Parma has 26 bike sharing stations and this service is widely used, in particular by commuters, students, or tourists. The main goal of this activity is to have an overview on how the bike sharing service is used and to evaluate if it is better to put some new bike sharing stations or it is more convenient a mixed system, with fixed stations and free floating.
- Radio-Frequency IDentification (RFID) access management: In 2019, the city of Parma decided to introduce IoT-based technological advancements to the existing mobility services, in order to provide a better experience to users. The city of Parma dematerialized the permits to access the city center of cars and logistics operators. The traditional paper permit has been replaced with a new, technologically-advanced pass, equipped with a microchip with RFID technology, which represents a sort of digital identity of the vehicle, that in the future will be used also for different purposes. The pass will be indeed enriched with new services related to the world of mobility, such as easy parking, “alert system” communications, and much more. The new electronic pass, created with the aim of simplifying, speeding up and facilitating the procedures for issuing and renewing permits, has allowed the complete dematerialization and automation of transit and parking permits in use.
- Magnetic parking sensor (drowned in parking stalls): this sensing node is able to detect the parking lot’s status change (free-to-busy, busy-to-free).
- Vehicle passage counting sensor: this sensing node returns the amount of vehicles transited bidirectionally, on a predefined time interval, along the road in which it has been mounted.
- Sensor for waste bins status monitoring: this sensing node is able to collect information about the bins filling level (based on 4 thresholds) together with a timestamp of the event, thus providing various additional estimations (e.g., time percentage in which the waste bin has been filled on a certain level, as well as full, average filling level in a certain city zone, and emptying frequency and last emptying).
- Sensor for counting the passage of people: this sensing has been used to estimate the average statistical amount of people passed in front of the sensor itself, on a predefined time interval, thus returning a statistical analysis on pedestrian traffic, and in case of unpredicted events (e.g., in case of crowed events), properly reroute people masses on less crowded areas.
- Environmental sensor (temperature, humidity, and pressure measurement): this sensor node is able to return the current environmental situation, while its data can be used as support to other sensing nodes, fusing together these estimations.
- Smart parking sensor based on optical technology: this sensing node is able to retrieve the status of different parking stalls in a monitored parking area with a timestamp.
- Sensor for measuring the environmental acoustic pressure: this sensing node is able to retrieve the average acoustic pressure level (dimension: [dB]) on a predefined time interval, thus providing an alert in case certain unpredicted events happen (e.g., intense traffic, road construction sites, etc.).
3.2. Sustainable Mobility
3.3. Occupation
3.4. Waste Management
3.5. Digital Transformation
3.6. Tourism and Cultural Aspects
3.7. Energy
3.8. Water and Air Quality
3.9. Legality and Security
3.10. Green Urban Areas
4. Smart and Sustainable Urban Mobility
- Support both local and isolated scenarios (not connected to the Internet), and fully on-Cloud architectures, in order to continuously collect a large amount of heterogeneous data from the city infrastructure [109], supporting several paradigms for data injection (e.g., on-demand data, proactive forward, scheduled forward, etc.) [110,111].
- Handle safety-critical scenarios, where involved entities (both IoT-related and not) should interact with the municipality’s control centers (e.g., traffic congestion area, pedestrian crossing paths, event mass moving) in a safe and secure way, even providing mechanisms to cope with the lack of connection/communication [112].
- Guarantee proper data management, according to data protections regulations [113] (e.g., the General Data Protection Regulation, GDPR [114]) and with respect of their ownership and protecting the involved entities [115]—as discussed in Section 3.9—against possible data threats (e.g., external intrusions, data tampering, Man-in-the-Middle (MITM) attacks, data sniffing, etc.), informing law enforcement agencies in case of data breaches [91,116];
- Provide distributed storage mechanisms, in order to decentralize the mobility network (and avoid bottlenecks often affecting centralized solutions), thus supporting efficient strategies for data retrieval and disaster recovery.
- Provide several easy-to-use visual consultation mechanisms for mobility data, through various representation technologies, based on the roles of the different users accessing them [119].
- Inform drivers and people on the street with dynamic signals (directly on the road) based on the environmental conditions sensed by local sensors; examples of these signals are speed limits, presence of speed meters, indications on traffic condition, and planning for public transportation [120].
- Collect traffic flow information through sensors deployed on the road, thus estimating some key features characterizing the mobility conditions: amount of cars passing a specific segment and density of trucks, cars, and motorcycles [121].
- Counting people’s density and flows moving in particular areas, through the usage of heterogeneous sensing nodes, based on heterogeneous sensors (such as optical and proximity sensors), and using IEEE 802.11 or BLE communication protocols [122]. As an example, these sensing elements could be placed in bus/train stations, cultural (e.g., museums) and crucial and strategic areas (e.g., train stations and airports).
- Prediction of free parking slots, delay of buses at bus stops, bikes to be shared from a given point, traffic flow at some points.
- Data visualization for mobility and transport control room operators, to transmit alarms in the case of early warning conditions and to monitor the current global traffic situation [123], in order to predict road traffic congestion and suggest alternative ways to reach a Point of Interest (POI) [124].
- ML-aided algorithms execution on traffic data, in order to suggest alternative paths for people in certain conditions, e.g., to avoid queues in congested areas and to promote new and alternative tours.
- AI-based algorithm execution for user behavior and engagement classification, in order to better understand how citizens use the city infrastructure and propose changes to promote virtuous behaviors [125].
- Flexibility: multiple modes of transportation allow travelers to choose which ones work best for a given situation.
- Efficiency: the trip gets the travelers to their destination with minimal disruption and in as little time as possible [130].
- Integration: the full route is planned door-to-door, regardless of which modes of transportation are used.
- Clean Technology: transportation moves away from pollution-causing vehicles to zero-emission ones.
- Safety: fatalities and injuries are drastically reduced.
5. Future Research Directions
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
AI | Artificial Intelligence |
AR | Augmented Reality |
BLE | Bluetooth Low Energy |
DDoS | Distributed DoS |
DL | Deep Learning |
DoS | Denial of Service |
GDPR | General Data Protection Regulation |
GIS | Geographic Information System |
GNSS | Global Navigation Satellite System |
GPS | Global Positioning System |
GW | Gateway |
H2H | Human-to-Human |
KPI | Key Performance Indicator |
ICT | Information Communication Technologies |
INS | Inertial Navigation System |
IoT | Internet of Things |
ITS | Intelligent Transportation System |
LPWAN | Low-Power Wide-Area Network |
M2M | Machine-to-Machine |
MITM | Man-in-the-Middle |
ML | Machine Learning |
NB-IoT | Narrowband IoT |
NFC | Near Field Communication |
NLP | Natural Language Processing |
PAN | Personal Area Network |
PED | Positive Energy District |
POI | Point of Interest |
RFID | Radio-Frequency IDentification |
SCAIP | Smart City Action and Investment Plan |
SDG | Sustainable Development Goal |
SEAP | Strategic Environmental Assessment Plan |
SECAP | Sustainable Energy and Climate Action Plan |
SDG | Sustainable Development Goals |
SUMP | Sustainable Urban Mobility Plan |
VANET | Vehicular Area Network |
V2V | Vehicle-to-Vehicle |
WLAN | Wireless Local Area Network |
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Citizens | Mobility | Environment | Governance |
---|---|---|---|
|
|
|
|
2017 | 2018 | 2019 | |||
---|---|---|---|---|---|
Indicator | Rank | Indicator | Rank | Indicator | Rank |
General | 9 | General | 8 | General | 8 |
Poverty | 1 | – | – | Economic Solidity | 8 |
Economic Growth | 19 | Economic Development | 14 | ||
Employment | 11 | Work | 7 | ||
Research and Innovation | 26 | Research and Innovation | 20 | ||
Water and Air | 64 | Water and Air | 102 | Environmental Protection | 18 |
Energy | 50 | Energy | 23 | ||
Waste Management | 12 | Waste Management | 10 | ||
Soil and Territory | 4 | Soil and Territory | 1 | ||
Urban Green Areas | 67 | Urban Green Areas | 86 | ||
Culture and Tourism | 27 | Culture and Tourism | 26 | Social Quality | 9 |
- | - | Social Inclusion | 1 | ||
Education | 31 | Education | 9 | ||
Digital Transformation | 22 | Digital Transformation | 9 | Digital Transformation | 8 |
Sustainable Mobility | 8 | Sustainable Mobility | 13 | Sustainable Mobility | 12 |
Legality and Security | 64 | Legality and Security | 22 | Governance | 7 |
Governance and Participation | 7 | Civic Participation | 13 |
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Share and Cite
Belli, L.; Cilfone, A.; Davoli, L.; Ferrari, G.; Adorni, P.; Di Nocera, F.; Dall’Olio, A.; Pellegrini, C.; Mordacci, M.; Bertolotti, E. IoT-Enabled Smart Sustainable Cities: Challenges and Approaches. Smart Cities 2020, 3, 1039-1071. https://doi.org/10.3390/smartcities3030052
Belli L, Cilfone A, Davoli L, Ferrari G, Adorni P, Di Nocera F, Dall’Olio A, Pellegrini C, Mordacci M, Bertolotti E. IoT-Enabled Smart Sustainable Cities: Challenges and Approaches. Smart Cities. 2020; 3(3):1039-1071. https://doi.org/10.3390/smartcities3030052
Chicago/Turabian StyleBelli, Laura, Antonio Cilfone, Luca Davoli, Gianluigi Ferrari, Paolo Adorni, Francesco Di Nocera, Alessandro Dall’Olio, Cristina Pellegrini, Marco Mordacci, and Enzo Bertolotti. 2020. "IoT-Enabled Smart Sustainable Cities: Challenges and Approaches" Smart Cities 3, no. 3: 1039-1071. https://doi.org/10.3390/smartcities3030052
APA StyleBelli, L., Cilfone, A., Davoli, L., Ferrari, G., Adorni, P., Di Nocera, F., Dall’Olio, A., Pellegrini, C., Mordacci, M., & Bertolotti, E. (2020). IoT-Enabled Smart Sustainable Cities: Challenges and Approaches. Smart Cities, 3(3), 1039-1071. https://doi.org/10.3390/smartcities3030052