Emergency Preparedness

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Authors

Brenda-Bannan.jpgJack Burbridge.pngMichaelDunaway.jpegDean Skidmore.jpeg

This section addresses the integration of traditional public safety and response into the broader scope of overall community preparedness, planning, and response. It deals with the development and coordination of multi-team systems of emergency response agencies with supporting and secondary organizations that interface directly with front-line responders during a disaster or civil emergency. Collectively, these organizations occupy the inner and second circles of Figure 2, and constitute the combined response capability of a community, jurisdiction, or region , and may be augmented by additional resources deployed through Emergency Management Assistance Compacts (EMAC) with adjacent states or jurisdictions or from federal sources, such as FEMA and other agencies.

Figure 2: Entities and organizations with responsibility for Public Safety

For technology solution providers, this section provides insight into EM workflows and decision-making priorities. Industry may better address EM needs by understanding the concepts, frameworks, and language EMs use. Technology solutions should address identified gaps in a way EMs understand and manage crises and disaster operations. Therefore, this section begins with an overview of emergency management models and best practices that will inform development of a shared language for identifying and articulating fundamental EM requirements.

For EMs, this section provides insight into the relevant data, tools, and technology solutions available to meet their needs and ways to effectively evaluate and integrate technologies and associated protocols. Goals include:

  • Improve EMs’ ability to evaluate and integrate S&CC/IoT technology into their emergency preparedness, management, and response processes—both for day-to-day operations (Blue-Sky days) and large-scale emergencies impacting multiple systems (Gray-Sky days).
  • Enable technology solution providers to better understand and address EM needs through meaningful use cases by presenting EM frameworks and language.
  • Suggest a collaborative, participatory process for design and integration of IoT solutions involving emergency management professionals, IT solution providers, and the community.
  • Provide examples of how existing IoT technologies can help provide solutions to city challenges.
  • Identify new vulnerabilities created by the connectedness of the previously unconnected first responder teams.

Key Characteristics

In general, the whole-of-community approach begins to have impact with emergency preparedness and management, where benefits from new technologies and the integration via advanced wireless networks supporting deployed sensors is most easily achieved. For preparedness, dual -use or multi-purpose technologies with utility in both Blue-Sky and Dark-Sky scenarios can achieve the greatest cost- effectiveness and potential for rapid adoption.

Key characteristics of the emergency preparedness and management approach to smart technology solutions include:

  • More diverse opportunities for identifying and defining requirements to improve public safety (i.e., a bigger marketplace) and higher likelihood that technologies can be adopted without disrupting operational readiness of critical agencies and community functions;

• Connection with critical infrastructure systems already undergoing fundamental technology upgrades and transitions, including the adoption of high-speed wireless networks, embedded IoT sensors, data-mining and social networking platforms, resilient electrical grids, and general access to commercial enterprises that support these systems; • Close relationship with both commercial and public research and development institutes, and a willingness to accept a certain amount of risk in technology investment; and, • Risk of developing or adopting systems incompatible with current systems used by first responders and agencies, or that require fundamental changes in operating doctrine or procedures among those agencies. Integrating S&CC and IoT technologies into the emergency preparedness process brings opportunities (such as better situational awareness) as well as complexities (such as increased volume and variety of data) for emergency managers. As communities adopt smart technologies, they must rethink policies, operating procedures, and interagency planning and communications for all phases of emergency management to fully leverage new opportunities. Similarly, while the S&CC/IoT technical community has made significant advances in developing technology solutions, they must incorporate input and context- specific validation from emergency managers (EMs) and related personnel to fully meet user needs.

Emergency Preparedness Models and Best Practices

Two current models serve as sound examples of operational systems for organizing emergency management and response structures: the U.S. National Response Framework and National Preparedness System, and the international Cluster System adopted by the United Nations. Both represent best practice foundations and a shared language for identifying and assessing emergency management needs, and may be adapted for use in S&CC for potential IoT integration and innovation. Successful smart technology solutions will address specific needs jurisdictions may have within these frameworks. In either case, similarity with existing operationally tested frameworks is a virtue and should be pursued in U.S. and international applications within S&CC to the extent feasible.

U.S. Model

The U.S. National Response Framework/National Preparedness System (NRF/NPS) model establishes a single, comprehensive approach to incident management within the U.S. The NRF is used to achieve the National Preparedness Goal of a secure and resilient nation with the capabilities required across the whole community to prevent, prepare for, respond to, and recover from terrorist attacks, major disasters, and other emergencies. The NPS preparedness cycle comprises the five key phases or mission areas of emergency preparedness and response: prevention, mitigation, response, recovery and protection. Within these phases are identified analysis and assessment actions include:

  • Threat and Hazard Identification and Risk Assessment (THIRA) – A four step common risk assessment process that helps a community develop a comprehensive hazard catalogue for threats and hazards of greatest concern, community defined desired outcomes, risk overview with hazard profiles and estimated impacts, and capability targets. There are 24 risk categories.
  • Core Capabilities Analysis – Communities engage in gap analysis planning efforts with capabilities falling into mission areas. As gaps are identified, specific needs emerge. Technology plays a role in helping EMs address these gaps within a core capability and across capabilities and in performing consequence analysis.

Technology solutions and innovations may enhance risk assessment through data collection and aggregation, modeling, predictive analysis, and dashboard views. Figure 6 shows the 32 core capabilities as they relate to the five mission areas of the NRF cycle. Hazard analysis is key to overall preparedness goals; planning and public information and warning are associated with all phases.

Figure 6: National Preparedness Cycle Mission Areas and Core Capabilities

International Models

When a large-scale emergency occurs, the capacity of a city, state or national emergency management infrastructure may be insufficient to handle the response alone. Therefore, in the international space, when multiple organizations respond, effective coordination among response stakeholders is essential for meaningful emergency management. Good coordination stems from effectively involving multiple teams and stakeholders and minimizing gaps and duplications in the response work across organizations. However, the need of inter-agency coordination expands to all phases of the crisis management from prevention to reconstruction and it is the core of large-scale emergency preparedness. To address this complexity of coordination across the diversity of organizations involved (e.g., governmental vs. non-governmental vs. voluntary), the domain expertise and skills required, and the varied tasks, United Nations has proposed a Cluster System11 as shown in Figure 7.

Figure 7: UN Cluster System

According to the United Nations Inter-Agency Standing Committee (IASC), the primary goal of this Cluster Approach is to strengthen system-wide preparedness and technical capacity to respond to large events or emergencies and to provide clear leadership and accountability in the main areas of emergency and humanitarian crisis response. At the nation level, it helps strengthen partnerships such as with the NRF in the U.S; and the predictability and accountability of international humanitarian action can be better understood with its help. By improving prioritization and clearly defining the roles and responsibilities of humanitarian organizations, the Cluster Approach has common features and synergies to NRF and NPS. The IASC guidelines and the UN Office of Coordination for Humanitarian Affairs emphasize:

  • Supporting service delivery by providing a platform for agreement on approaches and elimination of duplication;
  • Informing strategic decision-making for the humanitarian response through coordination of needs assessment, gap analysis and prioritization;
  • Planning and strategy development including sectoral plans, adherence to standards and funding needs;
  • Advocacy to address identified concerns on behalf of cluster participants and the affected population;
  • Monitoring and reporting on the cluster strategy and results; recommending corrective action where necessary; and,
  • Contingency planning/preparedness/national capacity building where needed and where capacity exists within the cluster.

The Cluster Approach objectives are like those of the NRF. In addition, in the international disaster response practice, the International Federation of Red Cross and Red Crescent (IFRC) Societies identifies the following elements in its comprehensive disaster preparedness strategic practices which can be adopted in a proposed model for defining preparedness requirements in a smart city context (Figure 8).

Figure 8: IFRC Elements for Comprehensive Disaster Preparedness Strategic Practices

City Emergency Management Needs and Resources

As emergency managers plan for and respond to emergencies, they see the need for smart technology solutions to support all phases of the NPS preparedness cycle or international preparedness models. To provide effective smart solutions for emergency management, technologists must understand EMs’ values, priorities, processes, goals, and specific requirements that support them, as well as the broader ecosystem of resources available. EM goals may include: reducing overall risk, knowing hazard asset impacts, automating awareness, and so on. For example, emergency preparedness and management involves coordinating information and professionals in a multi-team response with complex interdependencies of communication. resource sharing, and allocations to address any significant emergency such as an active shooter, terrorist attack, high-rise fire, and so on. The required multi-agency response demands enhanced situation awareness, judgment, and decision-making—providing an opportunity for IoT technologies to infor m emergency managers through real-time data collection and visualization as well as other potential capabilities. While all jurisdictions prepare for emergencies, the level of smart technology integration in this process depends on available resources, funding, experience, threats confronted, and other factors unique to each community.

Requirements

Participants in the March 2017 PSSC Workshop identified the following key requirements for technology solutions for emergency management and preparedness:

  • Shared Situational Awareness: The need for common platforms and operating procedures for all entities that share information and participate in emergency decision-making.
  • Governance: The need for a governance structure that defines smart city/IoT processes from procurement through implementation and ensures accountable oversight.
  • Collaboration: The need to bridge the gap between technologists and public safety personnel—finding a shared language based on a clear understanding of requirements and priorities.
  • Data: The need for planners to access the right data and make it actionable for emergency management and response.
  • Adaptation: The need to map solutions to existing emergency management frameworks and systems, rather than use “one-off” solutions, and to adapt to change.
  • Planning: The need to scale response capabilities to meet emergencies—technology can enable broader adoption. Scalability for scope and price in smaller jurisdictions is critical for broader adoption and longer-term commercialization of technologies.

Participants also identified technology design, development, and integration processes to address emergency management needs for:

  • Modeling and simulation:
    • Models for standardizing risk assessments and planning to:
      • Understand gaps in capabilities and resources against potential threats
      • Identify and prioritize threats and assess risk
      • Identify and link pre-assessment interdependencies
    • Resilience mapping, gross modeling, and simulation tools
  • Communications: Robust and interoperable systems and data that can lead to informed action, along with more human expertise across systems.
  • Information sharing: Full-scale situational awareness capable of integrating data from a broad range of systems, including open data, city-owned IoT, smart buildings, environmental sensors, and other sources.
  • Participatory, collaborative design, and innovation: involving all stakeholders and community members in design, development and integration of IoT technologies for emergency management.

Resources

PSSC Workshop participants identified the following resources that EMs utilize for preparedness. Technology solutions can also strengthen the management and integration of these resources and their accessibility to emergency managers.

  • Planning Models and Capabilities
    • Interoperable models and decision tools to enable:
      • Regional, national and international planning and risk assessment
      • Supply chain and logistics management
      • Management of communications resources
      • Post-disaster community recovery
  • Partnership Models
    • Mutual aid relationships
    • Integration of citizen resources, such as Citizen Corps Councils, Community Emergency

Response Teams, Medical Reserve Corps, Fire Corps, and Neighborhood Watch

  • Personnel and Facilities
    • Local and regional government-owned infrastructure
    • Privately owned infrastructure (telecommunications; transportation, etc.)
    • Business, financial and economic resources
    • Governance, community anchors, social services, and leadership

Adopting Technology Solutions to Address Emergency Management Needs

Priorities for technology solutions are focused on improving coordination among multi-team systems of responders; the integration of both public and private data and information into emergency preparedness practices (such as access and portability of critical medical data among patient populations), and similar challenges that have legal, proprietary, and security barriers, as well as policy implications.

Technology Requirements Development Process

As smart technologies expand the range of available data for EMs to make better planning and response decisions, solutions must meet EM requirements for how that data will be synthesized and used. Can EMs apply data within various forecasting models based on specific situations? Can they integrate different elements and run predictive analyses? Is the data presented in a way that EMs and incident command can effectively use? Do solutions enhance the effectiveness of intra- and inter-team communications and response?

An important objective is helping technology pr oviders fully understand the complexity of emergency response and the ecosystem of people, organizations, and resources involved so they can effectively address these demanding situations with technology applications and IoT innovations. Involving stakeholders in identifying problems and generating ideas, and enabling technology developers to immerse themselves in EM roles, context, and workflow is critical to meeting EM needs with targeted solutions. To articulate a broad process model that may consider local needs for emergency management, we must first consider the EM’s role and actions in identifying specific information needs and data management for effective visualization and response (see Figure 9).

Figure 9: Emergency Management Smart Technology Solution Evaluation

In this model, data management, security, interoperability, and other requirements such as reliability, scalability, and availability are required throughout the ecosystem. Solution features such as plug and play, multiple use, and ease of use are critical to acceptance.

Technologies should:

  • Draw upon data that can be acted on for emergency planning and response.
  • Improve the handoff of information across systems – including addressing handoff issues through simulation, training, and modeling.
  • Be based on open standards that enable interoperability for device interchangeability and data sharing.
  • Leverage non-government resources (e.g., business/community/region) and mutual aid (e.g., human and material resources).
  • Leverage dual or multi-use technologies where possible for improving ROI (for more information, see the later section on “Seeking Co-Benefits with Dual-Use Technologies.”
  • Provide user experience that meets specific public safety requirements in a range of environments and use scenarios.
  • Provide adequate training to optimize use and applicability in a wide range of scenarios.

Aligning Technology Efforts with City Needs

To ensure technology efforts align with city needs, technology solution providers should work with stakeholders to:

  1. Identify the problem to be solved within a recognized emergency management model, such as NRF, considering direct and secondary consequences of an emergency (for example, a water system failure impacts ability to fight fires) and the scope across phases from planning through recovery.
  2. Analyze available data and identify gaps in understanding or response. This may include an assessment of hazards, consequence, cross agency needs/assets analysis, impact analysis, GIS/mapping, and other existing data modeling/analysis.
  3. Identify specific requirements within core capabilities and gaps across the response spectrum that IoT/smart technology may address. This includes planning and response goals and technology needs analysis.
  4. Address the problem by repositioning, improving, or integrating existing technologies where feasible or innovating new solutions where necessary.
  5. Explore multi-use cases for solutions, addressing one or more core capabilities and primary and secondary benefits.
  6. Identify funding opportunities that can support initial implementation and sustaining operations.
  7. Build standards-based solutions so that data is interoperable by default.

Applied Research and Development Process

One model technology providers may consider is the applied research and development process for engineering smart city solutions, which incorporates a user-centered or user experience (UX) design and research approach. This is an iterative, progressive, and agile four-phase design process applicable for generating, refining, and scaling emergency management IoT solutions (see Table 1).

  • Research and Analysis – Elicits collaborative analysis and city assessment with citizens and stakeholders to establish a common vision for smart city innovation. This UX design process also permits emergency managers to work from established processes and frameworks familiar to them so that technology developers can intersect in this process to target their needs for UX smart city systems.
  • Ideation – Establishes a collaborative design process with citizens and stakeholders to elicit multiple perspectives on the problem, generate multiple design ideas, and prioritize and clarify the behavioral or performance targets aligned with meaningful data streams for smart city IoT innovations.
  • Refinement – Advances the generated prototype through establishing contextual relevance and usability via lab and field testing of the prototype, progressively refining and evolving the innovation, and establishing and expanding targeted metrics and measures to better determine return on investment or impact.
  • Solution – Incorporates methods to monitor and report out the initial design strategy as well as impact for learning about how the smart city solution was adopted, adapted, and integrated throughout the system. This phase can define incentives for use and impact on citizen’s lives as well as provide impetus for empirical investigation of the use, impact, and scaling of the innovation.


Case Study: Multiteam Interaction and Training of City-Wide Emergency Management

Identified Gap and Solution: In a city-based emergency or disaster, multiple teams—including emergency operations, FEMA, Department of Homeland Security, law enforcement, EMS, fire and rescue, and hospital trauma teams—must work together in a coordinated response. However, these teams rarely train together. Key to designing an effective multiteam smart IoT solution is understanding the impact of cross-team interaction and learning from team members’ real-world interactions as part of a larger city-wide system. To address this gap, Smart Emergency Medical Team Training developed an IoT system to improve the capture, analysis, and visualization of mobile behavioral data from proximity sensors worn by individual team members engaged in a multi-team, live simulation context. The objective was to identify and uncover important individual, team, and cross-team behavioral data and patterns (e.g. response time, proximity to the patient and, activity of individuals, teams, and representative of the overall multiteam system, etc.) to improve experiential learning during the debrief from cross-team interaction in high fidelity simulation training. The goal is to improve patient care, cross-team coordination and city services teams’ response time.

The Iterative user experience (UX) design and research process included:

  • Research. Through a multiteam training effort focused on extracting, treating and transporting a patient quickly to the hospital emergency room, the research team closely examined, generated, and evaluated best practices in emergency management, response, and healthcare disciplines to understand the context and problems through the users’ experience. From this analysis, prototyped IoT solutions were developed. An agile, flexible UX design process was leveraged aligning with the city’s core capabilities and risk assessments.
  • Analysis. Researchers conducted multiple, detailed investigations and observations of relevant user work processes in live simulations within and across teams to determine target audience(s), system requirements and to model usage, tasks and information flow. These provided the basis for user requirements for the system.
  • Ideation. The refined design goal, drawn from data analysis and generated design models, was directed at improving coordination, situational awareness, learning and performance of the multiteam system. The process strives to uncover the system requirements to iteratively design a system to meet team members’ work goals. In the use case, iterative design cycles continued in the development and integration of existing sensors and custom information systems toward the goal of visualized heterogeneous data sources (e.g. biometric body worn sensors, proximity beacons, 911 dispatch, GPS, GIS, and social media digital data) to provide information on inflection points between the teams—for example, when the patient is handed off from the EMS to the hospital trauma bay team.
  • Refinement. Refining the prototype represents the hard work of bringing an idea to life, progressively testing it through solicitation of targeted feedback and continually improving it through 1) progressive prototyping, 2) deploying, testing and evaluating the system and 3) adopting participatory design.
  • Solutions. The solution generated through a UX design and research process joins end user experience and knowledge with a design and prototype based on rich data from the context of use. The solution has improved ecological validity and is tested in context, thus demonstrating improved opportunities to transition and scale into other environments. While still in development, the project’s iterative prototyping with a participatory design process has garnered interest from other cities and expanded in scope. Deploying an early IoT solution prototype with iterative cycles of improvement permits other cities to consider the adoption, adaptation and diffusion of similar systems in their local contexts as well as provided additional input on the design and use.

Seeking Co-Benefits with Dual-Use Technologies

During an emergency, time matters. Smart systems/IoT solutions can bring information to decision- makers faster and with more fidelity than ever before , even when those systems are not purposefully designed for emergency management. Cities and technology developers can tap into this potential by considering the co -benefits to emergency management within their existing portfolio of systems and products. Systems designed for building security, energy management, and water/wastewater surveillance all have the potential to guide better decision -making during an emergency with limited additional costs.

As an example, many local jurisdictions use city buildings as sites for providing emergency shelter for displaced residents when their homes are not habitable following an emergency. During a large emergency that includes power outages, road closures, and other impacts, local jurisdictions must send out a representative to each potential shelter site to confirm that the facility is running, on primary or generator power, and the IT connectivity necessary to support operations. This information gathering requires time and slows the response.

At the same time, many jurisdictions are automating their building systems through sensors and other smart technology. The primary benefit of the system is to save operating costs, extend the lif e of those building systems, and reduce energy consumption. If these smart systems are already linked back to a central system for daily operations and management then that information can also lead to faster decision-making during emergencies. In our example, if the building sensors show that the building is on primary power with adequate IT connectivity, it allows decision-makers to select sites for emergency sheltering without sending a staff member to the site to evaluate it. This saves staff time and allows the shelter to open more quickly.

Guiding Questions

For Cities

  1. Has the city identified and prioritized key threats/hazards?
  2. Has the city identified key capability gaps and requirements?
  3. What are the city’s top emergency management needs and at what point(s) in the National Preparedness cycle do these occur? Where, when, and how does the city most need help?
  4. What information do city emergency managers need for preparedness? How should data be organized and analyzed to support emergency management and response? How should data be accessed for effective emergency management decision-making and coordination?
  5. After initial emergency response, what are secondary or other related needs of the city?
  6. Who are the different users of data from IoT solutions and what systems/platforms can be leveraged? Do we need to innovate (new technology), integrate (existing technologies), repurpose (leverage deployed technologies to meet new requirements)?
  7. What current or future IoT/smart solutions can support city emergency management and secondary needs, when in the cycle, how, and to what degree?
  8. What are the best current options for my city given available resources?
  9. What resources are available to obtain and use the solution? (capital and operational funding, personnel, training, etc.) What additional resources are needed now and in the future?
  10. What is the plan to sustain technology development and use into the future?

For First Responders and Response Agencies

  1. Based on the THIRA, what are the region's/community's key threats/hazards?
  2. Have responder agencies identified key capability gaps and technology requirements?
  3. What information do First Responders and Emergency Managers need, and when do they need it? How should data be organized and analyzed to support emergency management and First Responders? How should data be accessed for effective emergency management decision-making and coordination?
  4. After initial emergency response, what are secondary or other related needs of Emergency Management and response agencies?
  5. What data from IoT systems/platforms can be leveraged to improve situational awareness and decision-making? Must new technologies or applications be developed, or can existing technology systems be more usefully integrated to meet new requirements)?

For Technology Solution Providers

  1. Does the technology solution adequately reflect an understanding of what city EMs need at a situation-problem level?
  2. What specific threats and core capabilities does my solution address?
  3. How and at what point in an emergency does my solution help? (In preparation, protection, mitigation, response, recovery phases?)
  4. Does my system design meet industry standards, best practices and public safety end-user and responder requirements?
  5. Is the solution closed or open–how adaptable, scalable, replicable, cost-effective, easy-to-use is it?
  6. What additional/secondary benefits will the solution provide to city? How can the solution be applied to address broader city needs? (such as resilience, economic development, public health, community engagement, etc.)

Table 1: Applied Research and Development Process – Questions and Methods

Research and Analysis Ideation Refinement
Questions
  • What threats and hazards (from THIRA process) are of greatest concern for our community?
  • What are the relevant gaps and problems in our city and specific needs aligned with mission areas (e.g. prevention, protection, mitigation, response and recovery)?
  • How do we characterize or frame the problem with EM stakeholders and community members?
  • What are city-based networks, systemic, cultural, and social influences on problem?
  • What is the ecosystem of organizations, people, activities and places relevant to the identified problem?
  • Who is the targeted audience(s) for the smart city system?
  • How to build alliances/working/design groups, advocacy and trust for new ideas in this city?
  • What information can be gleaned or adapted from research, applications, in other cities?
  • How to connect gaps in capabilities and resources to potential threats for our city?
  • How to identify and link pre-assessment interdependencies?
  • What is the associated UX Smart City design goal, associated users and metrics that can define success for the system?
  • What data streams are actionable (and in what ways) for the identified city need?
  • Can we meaningfully integrate multiple data streams to inform the problem?
  • What are current communication, data, and information sharing systems?
  • What are possible future systems based on identified needs, applicable/potential data streams and available IoT/smart technologies?
  • What use cases or user story-maps may be conceptualized that demonstrate value of this system for our city?
Questions
  • How to include community members in a collaborative smart city design process?
  • What functional requirements fall from the integration of information from research and analysis?
  • How can we generate multiple ideas based on targeted needs and requirements?
  • What relevant behaviors, workflow, learning or performance targets are actionable for the targeted system innovation?
  • What are the relevant physical, contextual or ambient interactions among people, devices, and tasks given the targeted communication, data, and/or information sharing in this context?
  • What are functional segments of the design for relevant user tasks and how can these be integrated into a holistic system design?
  • What types of interactions are relevant (e.g. physical, movement, gesture, biometric, sound, etc.)?
  • How are specific requirements integrated into a holistic system to address the identified need?
  • What analytics or data streams can align with performance, behavior, or learning to measure improvement?
  • What is the connected device infrastructure –input and output of information flow?
  • How can we physically model and test parts of this system and iteratively evolve the conceptual design?
  • How do we narrow focus to generate ideas for a system proof-of-concept?
  • What are the usability and aesthetic design considerations of the system?
  • How can we create a coherent design across devices or contexts?
  • What are considerations for interface and visualization of actionable data (input, screens, displays, etc.)?
  • How is the system especially applicable for this city?
  • How can data streams be integrated and interoperable?
Questions
  • Is the enacted system usable and relevant to users, stakeholders?
  • How can we evaluate the prototype?
  • How can we progressively iterate from proof-of-concept to iteratively build and refine the system?
  • What elements of the system should be refined, eliminated, or revised?
  • What city-level ROI, measures, or metrics are applicable?
  • What are the system levers, drivers, or outcomes that can demonstrate impact on the city problem?
  • What city impact or system effectiveness can be determined?
  • How to grow and scale the system?
Methods
  • THIRA assessment
  • Core capabilities analysis
  • Analysis of smart city readiness
  • Service ecology or ecosystem mapping
  • Planning and strategy development
  • Identify stakeholders and networks
  • Needs assessment/gap analysis
  • Problem definition
  • Define smart city design goals, metrics and targets
  • Personas
  • Prioritization of needs
  • User Experience (UX) Design Inquiry
  • Contextual inquiry and analysis
  • Comparative analysis
  • Bottom up/top down work flow analysis
  • Surveys
  • Observation/Focus groups
  • Interviews
  • Benchmarking
  • User Journeys or story-mapping
  • Use cases
  • Case studies
Methods
  • Participatory Design
  • Requirements analysis
  • Cognitive task analysis
  • Identify workflow, learning and/or performance targets and outcomes
  • Network, system flows and feedback loops
  • Framing and reframing problem
  • Idea generation
  • Modeling workflow, interactions, communications, data flow, etc.
  • Design informing models – environment, social and process flow models
  • Generative design methods – sketching, storyboarding, user journey mapping, etc.
  • User walk-throughs
  • Heuristic evaluations
  • Expert Panels
  • City visits
  • Modeling
  • Simulation
  • Best Practices generation
  • Technical workshops
  • Iterative design
  • Engineering infrastructure diagrams with available internet-enabled devices and data streams
  • Prototyping
  • Alignment of behaviors and performance outcomes with data streams
  • Design reviews with citizens, stakeholders
Methods
  • Iterative feedback on conceptual design
  • Citizen critique
  • Cognitive walkthroughs
  • Iterative field testing of prototype
  • Hardware engineering and testing
  • In-situ product testing
  • Evaluation methods such as: feasibility testing, pilot testing, usability testing, expert review, formative evaluation
  • Determine relevant applied and empirical research methods such as: observation, video analysis
  • Identify metrics and outcomes at various levels of city system
  • Document design reviews
  • Iterative and agile revision

Adapted from:

Ratti, C. & Claudel, M. (2017) The city of tomorrow: Sensors, networks, hackers, and the future of urban life. New Haven, CT: Yale University Press.

Townsend, A. (2013). Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia. W.W. Norton & Company.

Hartson, R. & Pyla, P.S. (2012) The UX Book: Process and guidelines for ensuring a quality user experience. New York: Elsevier Morgan Kaufman.

Rowland, C., Goodman, E., Charlier, M., Light, A. & Lui, A. (2015). Designing connected products: UX for the consumer internet of things. Cambridge: O’Reilly Media, Inc.