- Data Categories
Agriculture Data 
B2B Data 
Biometric Data 
Company Data 
Conservation Data 
Demographic Data 
Economic Data 
Environmental Data 
Geospatial Data 
Healthcare Data 
Individual Data 
Industry-Specific Data 
Internet of Things (IoT) Data 
Legal and IP Data 
People and Employment Data 
Political Data 
Psychology Data 
Real Estate Data 
Retail & Commerce Data 
Social Data 
Space Exploration Data 
Sports & Entertainment Data 
Web Data
- Data Categories
- Agriculture Data
- B2B Data
- Biometric Data
- Company Data
- Conservation Data
- Demographic Data
- Economic Data
- Environmental Data
- Geospatial Data
- Healthcare Data
- Individual Data
- Industry-Specific Data
- Internet of Things (IoT) Data
- Legal and IP Data
- People and Employment Data
- Political Data
- Psychology Data
- Real Estate Data
- Retail & Commerce Data
- Social Data
- Space Exploration Data
- Sports & Entertainment Data
- Web Data
Smart Cities
How Is External Data Used in Smart Cities?
Smart Cities rely on external data: proprietary, public, and often open-source. In addition to general data categories like the weather and the census, smart cities use data from a complex network of sensors and devices that provide highly localized information on movement, utilities, and more. CCTV and acoustic sensors, for example, identify criminal behavior. Meanwhile, underground sensors placed beneath parking lots provide information on parking availability. IoT device-equipped cars communicate with each other about their location, acceleration, and more to reduce the chance of accidents. The examples go on.
How are Machine Learning Models Used in Smart Cities?
Smart cities need machine learning programs to function: firstly, because no human can analyze the sheer amount of data (even de-centralized)—especially not in time to resolve emerging problems. Secondly, these programs identify patterns—of criminal activity, of electricity usage, etc.—which city planners can use to improve that aspect of life.
Which Companies Lead the Way in Building Advanced Analytics and Machine Learning Products in This Field?
Data Alliance provides crowd-sourced block-chain IoT data for governments, municipalities, and others. In less than a year since its inception, it became a Gold Member of the Open Connectivity Foundation.
Commscope offers a wide range of sensors (fiber, cellular, WiFi, converged network management, etc.) to run a smart city. They also offer the services of consultants, local distributors, and other professionals who can help set up and manage the smart city ecosystem.
Siemens Smart Infrastructure focuses on providing industrial services to smart cities. In particular, they provide electricity and major smart power grid system services.
Connected Datasets
PipeCandy eCommerce Leads & Insights for Fulfillment
PipeCandy eCommerce Leads & Insights for Fulfillment tracks company data and company shipping details: shipping volume, which companies they use to ship products, whether they ship internationally or not, and so on. You can find company leads easily with this dataset with filter capabilities.
Wikiroutes Transit Data
Wikiroutes Transit Data provides public transport information—routes, stop points, and more—via crowd-sourcing. The data is constantly updated and can be easily converted and integrated into your own software system.
Wikiroute’s Transit Data is used by individuals, private companies, and government agencies of all types and sizes.
TrackStar Predictive Credit Technology
TrackStar’s Predictive Credit Technology uses fifteen years of financial dispute data to create predictive models of future borrowing potential. With this data and AI technology, your bank or other lending company can mitigate the risk of fraud, improve existing customer relations, and reduce your operating costs.