## 8 Importance of Blockchain and Big Data Analytics in IoT
### Big Data Analytics in IoT  
Over the past several years, the IoT has become an integral part of our daily lives. A large number of sensors or intelligent gadgets have been combined to link humans to the real environment, generating vast amounts of sensing data in the process. IoT device data is gathered, distributed, and transferred among individuals, businesses, and society. The quantity of data created by enterprises or people has increased considerably as a result of the growth of IoT. Despite the great benefit of the huge amount of data created in the IoT environment, researching and utilising this data's amazing worth will increase the danger of privacy violation [129]. The acquisition, storage, and reuse of data for financial gain presents a severe danger to privacy. As a result, researchers have the difficult task of ensuring data utility while maintaining privacy. In order to preserve data privacy, a variety of strategies have been created. These data privacy approaches may be classified into three categories depending on the stages of the big data life cycle [130].  
IoT systems are made up of a large number of devices and sensors that interact with one another. The number of these sensors and devices is continuously expanding due to the significant growth and extension of the IoT network [131]. These gadgets connect and send large amounts of data via the internet. This data is massive and updated every second, earning it the moniker \"big data\". With the continued growth of IoT-based networks, complicated issues such as data management and collection, storage and processing, and analytics can arise [132]. An IoT big data framework for smart buildings may help with a variety of challenges in smart buildings, including monitoring oxygen levels, measuring smoke and hazardous gases, and determining brightness. Such a framework is capable of collecting data from building sensors and doing data analytics for decision-making [133]. Furthermore, an IoT-based cyber-physical system equipped with information analysis and knowledge acquisition methodologies might boost industrial productivity. In smart cities, traffic congestion is a major concern. IoT devices and sensors embedded in traffic signals can collect real-time traffic information, which can then be processed in an IoT-based traffic management system [134].  
In healthcare analysis, IoT sensors attached to patients create a large amount of data regarding their health status every second. This vast volume of data must be consolidated into a single database and analyzed in real-time to make rapid, accurate decisions, and big data technology is the best tool for the task. In conjunction with big data analytics, IoT can also aid in the transformation of conventional industrial techniques into new ones [135]. Furthermore, cloud computing and analytics may aid in the development and conservation of energy while lowering costs and increasing customer satisfaction. IoT devices create a large volume of streaming data that must be efficiently stored and analyzed to make real-time decisions. Deep learning is particularly adept at dealing with enormous amounts of data, and can produce very accurate results. As a result, combining IoT, Big Data Analytics, and Deep Learning is critical for the development of a high-tech civilization [136].