Dark Mode
Futuristic Smart City Citizen Activity Data
Data Science and Analytics
Tags and Keywords
Trusted By
"No reviews yet"
Free
About
The daily activities of citizens within a futuristic smart city. It encompasses various aspects of urban life, including demographics, mobility patterns, lifestyle and social engagement, health and well-being metrics, and indicators of energy consumption and sustainability. The data is suitable for data analysis, machine learning, and visualisation projects related to urban mobility, sustainability, health trends, and behavioural analytics.
Columns
- Citizen_ID: A unique identifier for each citizen.
- Age: The age of the citizen, ranging from 18 to 70 years.
- Gender: The reported gender of the citizen (Male, Female, Other).
- Mode_of_Transport: The daily transport mode used by the citizen (e.g., EV, Public, Bicycle, Walking, etc.).
- Work_Hours: Hours spent working per day.
- Shopping_Hours: Hours spent shopping per day.
- Entertainment_Hours: Hours spent on entertainment per day.
- Home_Energy_Consumption_kWh: Daily energy consumption in kilowatt-hours.
- Charging_Station_Usage: An indicator (1 for yes, 0 for no) of whether the citizen used an EV charging station.
- Carbon_Footprint_kgCO2: Estimated daily carbon footprint in kilograms of CO2.
- Steps_Walked: The number of steps walked by the citizen.
- Calories_Burned: The estimated calories burned by the citizen.
- Sleep_Hours: The number of hours the citizen slept.
- Social_Media_Hours: Hours spent on social media per day.
- Public_Events_Hours: Hours spent attending public events per day.
Distribution
The dataset contains 1000 rows and 15 columns. It is available in a CSV file format, named
smart_city_citizen_activity.csv, with a file size of 62.25 kB. The dataset is not expected to be updated.Usage
This dataset is an excellent resource for:
- Analysing citizen behaviour trends.
- Understanding sustainable urban mobility.
- Predicting energy consumption patterns.
- Identifying health and social media habits.
- Developing machine learning models for smart city applications.
- Creating visualisations to represent urban lifestyle dynamics.
Coverage
The dataset focuses on the daily activities of citizens within a futuristic smart city. It includes demographic details such as age (18-70) and gender (Male, Female, Other). The information reflects daily activities without a specific stated time range, implying a snapshot or typical day for the population.
License
CC0: Public Domain
Who Can Use It
This dataset is suitable for a wide range of users, including:
- Data analysts looking to uncover trends in urban living and citizen behaviour.
- Researchers studying smart city development, urban planning, and sociological behaviours related to mobility, energy, and lifestyle.
- Machine learning engineers developing predictive models for energy consumption, mobility patterns, and health outcomes.
- Urban planners and policymakers seeking insights for sustainable city initiatives and citizen engagement strategies.
- Developers creating applications related to health, environmental impact, or citizen services in smart cities.
Dataset Name Suggestions
- Futuristic Smart City Citizen Activity Data
- Smart City Urban Dynamics Dataset
- Citizen Lifestyle and Mobility Records
- Urban Activity Metrics for Smart Cities
- Daily Habits Smart City Data
Attributes
Original Data Source: Futuristic Smart City Citizen Activity Data
QUALITY