
Explore how to design citizen-centric platforms in smart cities using retrieval augmented generation and serverless vector databases, powered by GPT-4 and Gemini Alpha, to address citizens' needs and congestion.
Meet a global co-creation authority who shares his journey and credentials in smart city innovation. Explore retrieval augmented generation within smart city contexts.
Explore advanced smart city engineering by building city platforms through retrieval augmented generation with GPT-4, developing insights and solutions that address residents' needs.
Explore how to develop RAG systems and build novel city platforms with generative AI to address emerging urban needs in smart and sustainable cities.
Outline the four chapters: building smart cities with generative AI, novel city platforms, databases and schemas for data and AI, and global case studies.
Explore the core urban infrastructure challenges facing modern cities—demographic, socio-economic, technological, environmental, and financial—and how quality services, management, and sustainable planning address congestion, housing, and access to public transport.
Explore how next-gen city platforms address quality of life, attractiveness, and competitiveness in the age of AI, by meeting housing, health, social, and economic needs beyond traditional smart city services.
Explore the physical components—roads and utilities—and the digital layer—data sensors and apps—and introduce five platforms: funding access, social life, relationship building, personal capacity, and access to machines.
Examine collecting and structuring city data for databases using sensors, online forms, and citizen input to support a retrieval augmented generation system and smart city applications.
Explore how to select and prototype a smart city service using retrieval augmented generation and ai prompts, guiding database design for a community carpooling transport service.
Design a database schema to collect citizens' health data and ride-sharing traits for novel insights, guiding edge data collection, vector storage, and retrieval augmented generation.
Develop a database schema for a community carpooling service, outlining tables such as users, vehicles, routes, ride requests, and ride offers, with dummy data, prompts, and vector embeddings testing.
Iterate on the city service database schema, generate five dummy entries with a guided prompt, and convert the data into a vector database using Pinecone and OpenAI.
Explore how cities collect data beyond sensors and edge devices, using Google Forms and web platforms to gather unstructured data like text, audio, images, and video.
Collect real-world data for a carpooling database with Google Forms, capturing user IDs, names, emails, phones, status, vehicle IDs, and route details; link to Sheets for live data with timestamps.
Store data in a vector store for retrieval augmented generation in smart city engineering. Learn how this approach enables efficient data retrieval for intelligent city applications.
Learn to set up the OpenAI and Pinecone APIs, create an OpenAI account, convert a database to a vector database, install libraries, and run data.py and query.py to test.
Upload data to a vector database with data.py, using LangChain, Pinecone, and OpenAI embeddings to load Excel, PDF, and CSV files, chunk documents, and index them as vector test.
Engineer a retrieval augmented workflow by querying a vector database with OpenAI embeddings, LangChain, and Pinecone to fetch the top three similar documents and answer transport problems via GPT-4 Turbo.
Build a retrieval augmented generation system by connecting a vector store to AI models like GPT-4 and Gemini, enabling semantic search and context-aware insights via LangChain.
Learn to build a custom GPT system with a paid account, connect to a database, and tailor responses using proprietary data and instructions by creating and configuring GPTs for tutorials.
Build a middleware to connect a custom GPT to a vector database, translating embeddings into natural language for chat with ChatGPT via an API using Flask, LangChain, Pinecone, and OpenAI.
Deploy your API to DigitalOcean's app platform by linking GitHub, selecting affordable plan, configuring the running command and OpenAI API key, and obtaining a live API URL for Postman testing.
Connect a custom gbdt to middleware by defining a schema, linking API endpoints and privacy policy, then test data queries from a vector database for accurate, scenario-based answers.
Connect a retrieval augmented generation system to a vector store to answer citizens' health, transport, and city queries; start with a custom GPT and move to independent interfaces.
Measure the accuracy of data-driven insights and explore monetization strategies for a long-term smart city retrieval system, covering databases, data stores, payment gateways, and data quarries.
You learn to build new smart city platforms using Rag technology to reveal insights from data and imagine novel city systems.
Explore how smart city engineering uses retrieval augmented generation and AI to design safer, more inclusive cities where people belong, boost social life, and improve transport services.
Explore how citizen-centric smart city platforms address affordability, inequality, mental health, and belonging, highlighting novel approaches for empowering young people to thrive in cities.
Introduce chapter two by exploring novel city platforms that design citizen-centric smart cities while addressing affordability and wealth inequality, mental health, and belonging for young people.
Outline the core structure for citizen centric smart city platforms, detailing five platforms and related database schemas.
Explore how smart city design addresses psychological needs and Maslow's hierarchy to foster safety, belonging, and self-actualization through five novel platforms integrating digital and physical solutions.
Explore how modern cities must prioritize Maslow’s psychological needs and self-actualization by designing five platforms, both digital and physical, to help youth access funds, safety, relationships, capacity, and production enablers.
Explore a funds-access platform that maps youth skills to opportunities, offering pathways for entrepreneurship, talent development, and capacity building in diverse city ecosystems.
Explore smart city platforms that provide access to funds through job portals, co-creation platforms and a workstation, and social networks, emphasizing skills registration, entrepreneurship education, and ongoing opportunity discovery.
Smart city platforms foster a social, vibrant life by providing regular, structured gatherings with clear meeting templates, agendas, and participant contributions, beyond traditional social media.
Explore how smart city platforms enable youths to access funds via co-creation workstations, job portals, and social networks through skill registration and entrepreneurship education.
Develop smart city platforms that safely facilitate love and intimate relationships by designing social scripts. Build trust with endorsement and security checks in culturally aware urban networking.
The lecture explores smart city platforms for love and intimate relationships, addressing gaps in physical, social, and digital options with contact methods, social scripts, and meeting templates to boost compatibility.
Discover smart city platforms that measure and boost personal capacity across physical, intellectual, social, and emotional dimensions using data-driven pathways and examples like Coursera, Udemy, and Toastmasters.
Advance personal capacity through smart city platforms combining physical and digital resources—gyms, universities, social clubs, and online courses—with capacity assessments and development plans to grow emotional intelligence and self-actualization.
Provide access to production machines and spaces to empower creation and prototyping. Foster city hubs that enable prosumers, producers and consumers, supporting smart city sustainability.
Explore a fifth platform granting access to machines, tutorials, and supervisors to help people develop product ideas with shared tools, backed by market data and database schemas.
Explore the details of chapter three's database schemas and preview the chapter structure, as the course outlines four to five chapters and a fifth on Rag systems applications.
Explore chapter three of smart city engineering, focusing on databases for city platforms and how data supports job stations, social platforms, and space database schemas to deliver insights and services.
Explore databases for job stations to collect CVs, user capacity, and opportunity data, delivering tailored postings and continuous work recommendations, backed by trust, reviews, and city wide opportunity management.
Frame the workstation database to link user profiles—skills, education, portfolio, certification—to opportunities, while maintaining an opportunities table with titles, descriptions, required skills, and funding.
Explore database schemas for a social platform that fosters affiliation, identity, and community via template-driven meetings, media creation, and group data, capturing user profiles, interests, events, and norms.
Build a relationship platform database capturing needs, capacity, and attraction metrics to enable initial contact, track meeting outcomes, and assess trust and compatibility over time.
Explore the relationship platform’s database schema that links relationship needs with personal capacities to match social, financial, and intimacy preferences, including trust scores, meeting requests, and progress tracking.
Explore a database schema for capacity building platforms that profile citizens across physical, intellectual, environmental, emotional, social, and spiritual capacities and collect data on fitness, education, speech, stress, and relationships.
Explore the fourth platform for personal capacity development, detailing user profiles and metrics across intellectual, emotional, social, spiritual, physical, and environmental capacities, plus data collection, growth plans and surveys.
Develop a production spaces database schema that captures users, machines, market data, tutorials, and digital interaction data. Use the data to guide production and profile outcomes by machine and user.
Explore databases about city machines, market data and trends, and tutorials, linking user profiles, machine and workshop data, and skill development with personalized recommendations and reviews.
Examine database schemas across smart city platforms—from job and funding to security, social, and relationship databases—and how they build personal capacity while connecting citizens to production machines and learning resources.
Develop databases and schemas for workstations, job centers, and social platforms; collect data for relationships, social needs, and capacities, and use platforms to enhance personal capacity and access production machines.
Explore global case studies of modern smart city platforms, examining social infrastructure, citizen relationships, and capacity building, and compare these platforms with the co-creation movement to advance SDGs and innovation.
Explore five chapter sections on global smart city concepts, platforms, and citizen access hubs. Compare visions from Neom, Masdar, Japan, and South Korea to see how smart cities differ worldwide.
Explore how mega city projects integrate job stations, access to funds, security, and co-creation to spur innovation, with Masdar City, Songdo, and Kashiwa as global case studies.
Explore global mega city projects, case studies like Masdar City, Songdo, and Kashiwa, and analyze how advanced technology and sustainable energy shape funding, innovation testbeds, and long-term socio-economic viability.
Examine how workstations, shared workspaces, and incubators, alongside online learning platforms like Udemy and Coursera, expand access to opportunities, funding, mentorship, and markets in smart city development.
Explore how shared workspaces, incubators, and online learning empower smart cities, from WeWork and the co-creation movement to mentorship, funding access, and platforms like Coursera, Udacity, and Udemy.
Examine diverse workstations beyond traditional hubs, including public libraries like Dokk1, innovation hubs, and affordable housing models that accelerate access to funds and opportunities via social enterprise.
Explore how innovation ecosystems and platforms like T-hub, libraries, and affordable housing enable access to funds and opportunities, foster co-creation, and build community infrastructure for startups in smart cities.
Explore global case studies of social platforms, from mosques and universities to carnival communities and co-creation cafes, and examine how identity and gathering shape urban life.
Examine social platforms that act as workstations—incubators, shared spaces, and hubs like T-hub, Dock one, Urban rigger, and Impact Hub—unlocking funds and opportunities in smart cities.
Explore stadiums, theatres, and religious festivals as city social platforms that foster belonging, affiliation, and entertainment through cultural activities.
Explore social platforms in the city, from the co-creation movement and its state of the movement events to stadiums, theatres, and religious festivals like Diwali, promoting social action and culture.
Explore how city platforms—from mosques and universities to museums and festivals—address social needs, while the co-creation movement promotes togetherness, trust, inclusion, and ongoing social action.
Explore how social platforms in cities and museums tell civilization stories through art, culture, and infrastructure, while digital platforms enable social interaction and targeted engagement without prioritizing physical meetings.
Explore relationship platforms, including Tinder, and analyze how social scripts and cultural norms shape initial contact, romance, and family-building in urban contexts.
Explore a novel relationship platform designed to be safe, culturally appropriate, and data-driven, enabling initial contact, group requests, and meaningful connections within city life.
Explore how capacity building platforms help young people improve personal capacity, covering intellectual discourse, emotional intelligence, public speaking, social networks, physical fitness, and environmental and spiritual capacity.
Examine capacity building in cities through platforms that grow intellectual, financial, social, emotional, and spiritual capacities, with examples like Coursera, Duolingo, gyms, and libraries.
Explore production space platforms that grant access to production machines like 3D printers, milling, and CNC, through cases including MIT Fab Lab, Shenzhen Open Innovation Hub, and US Tech Shop.
Production space platforms unlock access to machines—like MIT Fab Lab and Shenzhen Open Innovation Lab—enabling young people to prototype ideas into robots, electronics, and products under supervision.
Explore examples of novel platforms and smart cities, including co-working spaces, incubators, online platforms, festivals, museums, and social clubs, united by the co-creation movement to meet security and social needs.
This course is a smart city engineering course that aims to help you design novel smart city platforms with the help of retrieval augmented generation (RAG) and vector database. In this course you will learn how to think about the city citizen centric needs and how to address these needs in an effective manner using physical and digital platforms. The course outline will cover the following topics:
- Chapter 1: Building Smart City Platforms – Using AI
- Chapter 2: Building a Citizen Centric Smart City Platforms
- Chapter 3: Building Databases for Modern Smart City Platforms
- Chapter 4: Modern Smart City Platforms – Global Case Studies
- Chapter 5: Practical Applications USING RAG technology.
We will study global cities and the various platforms of social activities they conduct to address their citizens needs. We will look carefully into the following platforms:
•Section 1: Workstations – Global Case Studies
•Section 2: Social Platforms – Global Case Studies
•Section 3: Relationship Platforms – Discussion
•Section 4: Capacity Building Platforms – Global Case Studies
•Section 5: Production Space Platforms – Global Case Studies
In this course, you will learn how to design database schemas, how to collect data from the city and how to transfer this data into vector embeddings and store it in a vector datastore. This will result in giving you the ability to apply Retrieval Augmented Generation search using Large Language Models such GPT4 and Gemini.
This course is seen as one of the most advanced courses in the world in this novel area, it will make a great difference on how much you can create.