Internet of Thing (IoT)
The Internet of Things (IoT) is a baby of three Internet, Wireless technologies and micro-electromechanical systems (MEMS). Each and every object in this earth can be uniquely identified because of the advent of IPv6’s huge address space and they can automatically transfer data over a network without any interaction of human-to-human or human-to-computer. As new system evolves, an increase in the number of smart nodes and the amount of data the nodes generate, need more requirements on data privacy, data sovereignty and security.
IoT can mashup data from multiple devices and enterprise systems with rich and real-time analytics to create deep insight on efficiency and opportunity. For example Iot advancements have made possible Smart Utility grids, mHealth and Patient Monitoring, Manufacturing Automation, Retail and Intelligent Supply Chain Management etc.
Features of IoT and Mobile Apps
Automation for lowering costs: using robots, smart trolleys to track shoppers around the store and in-store sensors make possible to place high margin products and reducing risks of theft in low cost as no human beings or security guards are payed extra money for watching or guarding the products.
Smart Vehicles with in-vehicle sensors connected to the engine bus that can track driver behavior, state of the vehicle and act accordingly to maximize fuel efficiency.
For Production lines or heavy plant equipment, constant diagnostics and real time analytics can be performed automatically to identify performance deviations, problems and schedule necessary and preventative maintenance.
To strengthen customer engagement using mobile apps
Create new revenue streams for mobile apps based on location or priority moments
Challenges of IoT and Mobile Apps
Requirement of new data storage architecture that need to be dynamic and flexible for embedding sensors on physical assets with emerging standards and updated regulatory controls.
Huge amount of various types of data from millions of Multiple Devices and sources should be able to incorporate rapidly for example, precisely targeted ads, promotions and offers should be delivered to users holding smartphones from different geographical locations with user preferences.
These system need to store and update billions of data and information each day which traditional or relational database cannot handle easily. By 2020, around 50 billion sensor-equipped smart objects will be in use. For example to report location of one million of vehicles every 60 seconds generate billions of data points in a day which traditional database cannot manage in such speed.
Automation in real-time supply chains, manufacturing process control and e-commerce supermarket needs deep insights by analying, visualizing and responding to sensor outputs for which powerful query tools are required to run complex queries on frequently changing data store.
Because of rigid structure of relational database, it is not possible to use for apps that needs to update frequently for example mobile apps are updated every month by Facebook to move with current innovation.
As MongoDB’s is not rigidly structured i.e. it has dynamic schema that enables new features can be easily added and removed as needed by developers.
Auto-sharding is another unbeatable feature of MongoDB that enables partition and scale rapidly growing data sets with very low cost around multiple servers with transparency.
Using Apache Hadoop distribution, BI (Business Intelligent) and Analytics tools with frameworks that supports complex query like secondary, geospatial, text search indexes, native MapReduce and Aggregation Framework, MongoDB can support rich and complex query across operational data for real-time insights and reporting to identify problems, handle or update change rapidly.
MongoDB can store documents which are flexible enough to represent multiple smartphone data types and complex user data with a single data store very easily.