IoT Data Storage and Event Handling

Study Notes

Software components assemble events, which include logic value, event ID, and device ID, and add a date-time stamp.
Events from IoT devices and logic flows are assembled using software.

A data store is a repository of a set of objects that integrate into the store.
Features of a data store:
- Objects are modeled using classes defined by database schemas.
- Can be distributed over multiple nodes.
- May consist of multiple schemas or data in only one scheme.
Examples of data stores:
- Database
- Relational database
- Flat file
- Spreadsheet
- Mail server
- Web server
- Directory services
- VMware

A data centre is a facility with multiple banks of computers, servers, and high-speed network and Internet connectivity.
Features of a data centre:
- Provides data security and protection using advanced tools.
- Offers full data backups and data recovery.
- Has redundant data communication connections and full system power and electricity supply backups.
- Meant for data storage, data security, and protection.
Large industrial units, banks, railways, and airlines use data centre services.
Data centre managers are responsible for technical and IT issues, operations, data security, data quality control, and network quality control.

Server management involves managing services, setup, and maintenance of systems associated with the server.
Key aspects of server management:
- Short reaction times when the system or network is down.
- High security standards through routine maintenance and updates.
- Optimized performance and monitoring of critical services.
- Security of systems and protection of data, files, and databases.
- Strict documentation and audit of all activities.

Spatial storage is optimized for storing and querying spatial data.
Spatial data refers to data that represents objects defined in a geometric space.
Examples of spatial data:
- Points
- Lines
- Polygons
Applications of spatial storage:
- Tracking or inventory control
- Digital maps for parking slots

Data can be categorized into three categories for storage:
- Data alone (for repeated processing, referencing, or auditing)
- Data and results of processing (for quick visualization and reports generation)
- Only the results of data analytics (for storage of processed data)
A fourth category, Big Data, is used for storing large amounts of data from multiple devices and sources.

A device can generate events, which are assigned an ID and a logic value.
Logic values:
- Logic 1: An event generated but not yet acted upon.
- Logic 0: An event generated and acted upon, or not yet generated.