Survey on Image Compression Techniques and IOT Challenges

Abstract

This paper presents the challenges faced in storage and transmission of big data images which are used for IOT networks. Internet of Things (IOT), is the interconnection of electronic devices and software. The devices which are connected in the network will have different sensors which are used for data collection. Each sensor will monitor a specific condition such as location, vibration, motion, temperature and visual data. Sensors of a device communicate over an IP Network with other devices. IOT-enabled devices will share information about their conditions with software systems, and other machines. This information can be shared in real time or they can be collected and shared at desired intervals. Due to IOT enabled devices, everything will have a digital identity and connectivity, which means one can identify, track and communicate with the devices. Machine-to-Machine communication intelligences drawn from the IOT-enabled devices in the network will allow businesses to automate certain basic tasks without depending on central or cloud-based applications and services. The number of devices, or nodes, that are connected in the network are bulk in IOT than in traditional systems. In IOT huge amount of data need to be collected and transmitted leads to challenges in terms of framing the data appropriately and providing security. Therefore, IOT data computations become complex and tedious. For simplifying the IOT data computations and fast transmissions, pre-processing techniques were used. Here we did a literature survey on pre-processing techniques such as image Compression and fusion techniques, which were used to make IOT computation simple.