I. INTRODUCTION

II. REALTED WORK

III. SYSTEM DESIGN

IV. CASE STUDY

V. CONCLUSION

REFERENCES

Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment.

INTRODUCTION

Recently, Internet of Things (IoT) has been widely applied in information technology (IT) which is a concept of connecting physical objects via networks for data collection and sharing. The ‘Things’ in IoT is defined as devices connected to the Internet and able to transmit information to other devices [1]. There are many systems that can be associated with IoT, including green agriculture monitoring system [2], intelligent transportation system [3], environment monitoring system [4], and applications in healthcare industry [5], etc. The connected health model was proposed as an IoT aspect of healthcare, and the applications of connected health are aiming to improve health care services [6]. Medical IoT is considered as a basis of connected health, where the data exchanging is achieved among doctors, patients and medical equipment [7]. Medical IoT can break the regional restriction to doctors, where medical data and case history can be shared. Meanwhile, the real-time monitoring and diagnosis of patients via Medical IoT greatly reduces the cost and time for transporting patients, and improves the cure rate of emergency diseases [8]. The medical big data is defined as a collection based on health-related data which is produced in the entire diagnosis process, from clinic registration to hospital follow-up of patients [9], [10].