The Internet of Things is made of diverse networked things (i.e., smart, intelligent devices) that are consistently interconnected, producing meaningful data across the network without human interaction. Nowadays, the Healthcare system is widely interconnected with IoT environments to facilitate the best possible patient monitoring, efficient diagnosis, and timely operate with existing diseases towards the patients. Concerning the security and privacy of the patient's information. This paper is focused on Secure surveillance mechanism for a medical healthcare system with enabled internet of Things (sensors) by intelligently recorded video summary into the server and keyframes image encryption. This paper is twofold. Firstly, a well-organized keyframe extraction mechanism is called to extract meaningful image frames (detected normal/abnormal activities keyframe) by the visual sensor with an alert sent to the concerned authority in the healthcare system. Secondly, the final decision about the happened activity with extracted keyframes to keep highly secure from any adversary, and we propose an efficient probabilistic and lightweight encryption algorithm. Our proposed mechanism verifies effectiveness through producing results, robustness in nature, minimum execution time, and comparatively secure than other images (keyframes) encryption algorithms. Additionally, this mechanism can reduce storage, bandwidth, required transmission cost, and timely analysis of happened activity from any adversary with protecting the privacy of the patient's information in the IoT enabled healthcare system.

The technological progression is raised as a hybrid ecosystem with the industrial Internet of Things (IIoT). Among them, healthcare is also broadly unified with the Internet of Things to develop an industrial forthcoming system. Utilizing this type of system can be facilitating optimum patient monitoring, competent diagnosis, intensive care, and including the appropriate operation against the existing critical diseases. Due to enormous data theft or privacy leakage, security, and privacy towards patient-based informative data, the preservation of personal patients’ informative data has now become a necessity in the digitized community. The produced article is underlined on handsomely monitoring, perceptively extracted keyframe, and further processed lightweight cosine functions using hybrid way chaotic map keyframe image encryption. Initially, a regular concept of extracted keyframe is deployed to salvage meaningful detected frames by transmitting an alert autonomously to the administration. Then, lightweight cosine function for encryption is employed. This encryption incorporates keyframe exceedingly secure and safe from the outside world or any adversary. Our proposed methodology validates effectiveness throughout the IIoT ecosystem. The produced outcome is highly acceptable and has minimum execution time, robustness, and reasonably adopted cost-effective, secure parameter than any other (keyframes) image encryption methods. Furthermore, this methodology has optimally reduced bandwidth, essential communicating price, transmission cost, storage, and immediately judicious analysis of each occurred activity from the outside world or any adversary to remain secure and confident about the real patient-based data in the smartly developed environment.

The heart of the current wireless communication systems (including 5G) is the Fourier transform-based orthogonal frequency division multiplex (OFDM). Over time, a lot of research has proposed the wavelet transform-based OFDM as a better replacement of Fourier in the physical layer solutions because of its performance and ability to support network-intensive applications such as the Internet of Things (IoT). In this paper, we weigh the wavelet transform performances against the future wireless application system requirements and propose guidelines and approaches for wavelet applications in 5G waveform design. This is followed by a detailed impact on healthcare. Using an image as the test data, a comprehensive performance comparison between Fourier transform and various wavelet transforms has been done considering the following 5G key performance indicators (KPIs): energy efficiency, modulation and demodulation complexity, reliability, latency, spectral efficiency, effect of transmission/reception under asynchronous transmission, and robustness to time-/frequency-selective channels. Finally, the guidelines for wavelet transform use are presented. The guidelines are sufficient to serve as approaches for tradeoffs and also as the guide for further developments.