Discovery’s Solution to 5 Major Existing IoT challenges
The Internet of Things is gaining momentum and transforming many industries say transportation, utilities, process, health and insurance etc. It is becoming the essential strength of every business sector and adopting IoT is aiding them in refining their business processes. Unfortunately, as the usage of IoT increases, various challenges are encountered and has own sets of caveats that need to be solved to meet the requirements. The 5 major existing IoT challenges are as follows :
Security has now become the crucial concern for IoT networks. As the number of connected devices are increasing, vulnerabilities to data theft is on the rise as a result of inadequate data protection standards. From hacking baby monitors to city infrastructure of Ukraine power grid hack, soon every industry will be affected. It has become difficult for IoT industries to keep the data secured while hackers find new ways to attack the cyber infrastructure.
Keeping in mind how security is vital, we are developing our blockchain IoT network that will address the gaping hole in IoT security. With the use of artificial intelligence, edge computing and decentralized DAG protocol, our IoT network will be highly secured. While decentralized architecture enhances cyber security through its consensus mechanism, AI can help in detecting any unusual activities in the network. Machine learning and AI will undoubtedly be integral to the future IoT security landscape.
Scalability means process of handling growing amount of work or its potential to be enlarged in order to accommodate the growth. Gartner says, there will be 20 billion connected devices in 2020, which eventually means that IoT networks must be scalable in order to accumulate these devices. In spite of residing on smartphones which is a crowded source, our blockchain 4.0 technology can handle large number of devices and also manage millions of transactions per second which will make our network massive and scalable.
3. Data storage and processing
IoT networks owes a volatile growth and the information is provided by the cloud service providers where the data is actually stored. Despite these services, cloud platform does not fit best for the certain environments where internet connectivity is poor or where the data processing needs time. This predicament with the cloud is solved with edge computing. We are developing a new breed of IoT network by replacing cloud computing with edge computing where the data processing will be done at the edge of the network instead of cloud or central warehouse. Having sensors everywhere helps to process data at the edge instead of sending it to the cloud and waiting for it to be processed.
4. Lack of intelligence
Edge Intelligence (EI) introduces a shift with respect to storing, acquiring and processing data. These data processing are placed at the edge between the data source and the IoT core and storage services located in the cloud. It comes with added benefits of
- Reducing bandwidth
- Minimizing latency
- Improving reliability
- Avoiding duplication
- Maintaining compliance
By providing solutions to all hurdles like connecting devices, understanding data, training AI, we are trying to emerge out in the market with innovative ideas aiming to lessen human interventions. Our core concept Edge Intelligence pushes communication capabilities and processing power directly into smartphones with the help of programmable automation controllers.
According to a report by McKinsey titled “Unlocked the potential of the internet of things”, interoperability is the missing stage to the progress of IOT. Issues that arise due to lack of interoperability in IoT devices are the inability to
- To secure devices using third party security software
- To monitor and manage devices
- To get information from the devices using same interface
As a blockless DAG based IOT network, we found that an ideal solution to this problem would be creating standards and supporting widely used protocols. Interoperability between IoT is complex, but the application layer is seen as the key place to get bridging technology to the layers below. From device manufacturers to software programmers and network administrators, there is a need for standards and protocols that explains the guidelines to all stakeholders. Some popular network protocols are TLS, IPv6, IEEE, RFC, IMAP, PPP and UUCP.