The internet of things (IoT) will be the next big thing in the evolution of our technology, with machine learning and artificial intelligence helping automate the operations of so many human affairs, helping humans save energy and run things in a more efficient manner.
IoT thrives and feeds on massive amounts of data, which dictates its operations. Big data helps IoT systems understand patterns of human behavior, which also determine its functions and responses. The data involved in IoT operations require large capacity, secure storage server systems.
This is where cloud storage comes in. Cloud storage can help overcome the capacity and security limitations of physical servers, which is highly suitable to accommodate the big data, which has enormous volume, variety and velocity. The cloud storage can also manage these things with a smaller lag time and less glitches.
The cloud serves as an ideal solution for mammoth-sized data management and retrieval not only due to its capacity, but also the way it handles data: cloud computing processes data efficiently by dividing it into smaller parts and performing different processing functions simultaneously. Cloud computing also offers a system which is more adaptable and resilient.
In this case, hybrid cloud is the best type for big data management, as hybrid cloud is the type which allows the breakdown and simultaneous processing of the big data, to allow quicker analytics processes as mentioned earlier.
Keeping this in mind, how can cloud IoT computing and big data maximize each other’s function?
The role of cloud computing in IoT and big data operations
An IoT system typically sends the data it has collected from various sensors to an analytics cloud to be processed through a gateway. The connection between the sensors and gateway is oftentimes created through radio frequency, wi-fi, wired connections and BLE. The gateway, meanwhile, can be any device, most frequently a mobile phone.
Through its extensive capacity to handle data volume, variety and velocity, the cloud computing system helps IoT to process the data more efficiently to perform time-sensitive functions and help the IoT runs its system more quickly.
This is especially important in detecting anomalies and sending alerts to users, especially in the “smart city”, “smart home” and “smart office” contexts. Use cases include fire/smoke warning, traffic congestion alerts or pollution sensors. With data on these things processed quickly, with less glitches and smaller lag time, thus resulting in quicker automated response (such as turning the fire extinguisher on or advising users to change route amid traffic congestion).
Challenges to cloud adoption to big data processing
There are several challenges to be overcome when using cloud computing to serve as a space for IoT and big data analytics. They are: enhancing the security and privacy of the (hybrid) cloud computing system, promoting data heterogeneity in the cloud computing system, as well as increasing the effectiveness of monitoring and performance.
All in all, if you want to boost your company’s IoT efficacy, then also invest in cloud computing to boost your organization’s data processing activities.
Was this information helpful?
Big Data will make it big in this very year. Several studies revealed that there were 40 times more bytes of data in the world than there were stars in the observable universe, according to fintechnews.org.
back to top