Smart City Academy

MODULE 1

IMPLEMENTING SMART CITY STRATEGIES: A POLICY AND STANDARDS GUIDE

  • Definition and Scope of Smart City Policies and Standards.
  • Importance of a Robust Policy Framework.
  • Overview of Existing Global and Regional Standards.
  • Formulating Smart City Objectives and Goals
  • Legal and Regulatory Considerations in Policy Development
  • Understanding Smart City Standards.
  • Importance of Interoperability in Smart City Solutions.
  • Adoption of Global and Local Standards.
  • Developing an Interoperability Framework.
  • Definition and Scope of Smart City Policies and Standards.
  • Importance of a Robust Policy Framework.
  • Overview of Existing Global and Regional Standards.
  • Anticipating Future Trends in Smart City Policies
  • Adapting Policies to Technological Advances
  • Integrating Emerging Technologies into Policy Frameworks
  • Analyzing Successful Smart City Policy Implementations.
  • Learning from Challenges and Failures.
  • Extracting Best Practices for Policy Design and Implementation.
  • Lessons for Continuous Improvement in Smart City Policies.

MODULE 2

BUILDING THE CITIES OF TOMORROW: TECHNOLOGIES, LESSONS AND FUTURE VISIONS

  • Introduction to the principles and practices of smart city planning.
  • Integration of advanced technologies for sustainable and efficient urban development.
  • In-depth analysis of foundational technologies influencing urban landscapes.
  • Exploration of the role of IoT, AI, blockchain, and other emerging technologies in shaping the cities of tomorrow.
  • Examination of sustainable infrastructure projects globally.
  • Implementation of green building practices, renewable energy solutions, and environmentally conscious urban design.
  • Visionary insights into the future of smart and sustainable transportation.
  • Case studies showcasing innovative mobility solutions, including electric vehicles, autonomous transportation, and urban air mobility.
  • Strategies for creating cities that are resilient to climate change.
  • Learning from cities that have effectively adapted and recovered from environmental challenges.
  • Exploration of data analytics and its role in smart governance.
  • Case studies demonstrating how cities leverage data for informed decision-making and citizen engagement.

MODULE 3

THE ESSENTIALS OF DATA POLICIES FOR SMART CITIES

  • Grasp the concept of CDP.
  • Understand the role of CDP in smart city development.
  • Recognize the stakeholders involved in CDP.
  • Identify the drivers for adopting a CDP.
  • Recognize the challenges and opportunities in data-driven urban governance.
  • Identify and understand various components like data categorization, classification, and security.
  • Learn about SOPs for data collection, processing, and publishing.
  • Understand the processes involved in implementing CDP.
  • Learn about governance structures and accountability mechanisms.

MODULE 4

THE ESTABLISHMENT OF INTERNAL DATA GOVERNANCE

  • Overview of data governance concepts, principles, and its importance in the Smart City context.
  • Exploration of various data governance models and their applicability to Smart Cities.
  • Discussion on laws, regulations, and policies impacting data governance in urban areas.
  • Comprehensive look at the data lifecycle from collection to disposal, focusing on data quality and integrity.
  • Analysis of data security measures, privacy concerns, and risk management in Smart City infrastructures.
  • Guidance on creating and enforcing data protection policies within a Smart City framework.
  • Examining ethical considerations in data collection, processing, and usage.
  • Utilizing data analytics and intelligence for informed decision-making in urban development.
  • Analysing real-world examples of successful data governance in Smart Cities.

MODULE 5

THE ESTABLISHMENT OF EXTERNAL OPEN DATA POLICY

  • Comprehend the importance and goals of open data in government transparency.
  • Recognize key terms and principles related to open data.
  • Identify legal requirements affecting open data publication.
  • Understand the alignment of open data practices with existing policies.
  • Master techniques for identifying datasets suitable for open data.
  • Understand the process of classifying data sensitivity.
  • Learn about dataset publication processes and documentation standards.
  • Understand the review process and requirements for derivative datasets.
  • Learn about dataset update schedules and data integrity.
  • Understand the process of modifying and archiving outdated datasets.
  • Learn about preferred data formats and identifiers.
  • Understand the alignment with national and international data standards.