## 4 IoT Contribution to Monitoring Systems
### Security Aspects of Data for IoT-Based Big Data Transmission & Management over the Cloud
Additionally, \(PL\) represents the value of the _packet loss rate_, \(T\) represents the value of the _Round Trip Time_, \(S\) represents the value of the _signal-to-interference and noise ratio_, and \(k\) represents the value of the _sequence number_ of the current time window. In the end, \(b_{k}^{first}\) represents the value of the _bandwidth of the first time window_, \(b_{k-1}^{first-1}\) represents the value of the _bandwidth of the first time window_-1, and \(b_{k+1}^{next}\) represents the value of the _bandwidth of the next time window_, which is the time we need. Counting on Equation (1) that we ended up with in our proposal, we can determine an algorithm that implements Equation (1). Another term that we combine with our Equation (1) to achieve the proposed algorithm is \(TW\), which represents the value of the _Time Window_. Moreover, we will also use LoK and LoA, which represent the value of the Layer of Keystone and the value of the Layer of Absorption, respectively. The proposed algorithm is presented in (Algorithm 2). Specifically, Algorithm 2 represents the whole procedure implemented by our proposed Equation (1), consisting of our study on previous works [6; 10; 11; 66; 73]. As a result, in Algorithm 2, we compare the data from the _First Time Window_ to the functions that depict the change in the value of each component of Equation (1). The suggested algorithm \"_calls_\" the value of the _Packet Loss Rate_, _Round Trip Time_, _Signal to Interface_, and _Noise Ratio_ of each loop in a limited number of loops while the time is \"_paused_\", all from the client that transmits and/or analyzes the video/image. Continuously, counting on Equation (1), the algorithm calculates a better way to transmit and/or process the video/image by choosing a calculation scenario relying on the type of the transmitted and/or processed video/image. Inside a loop function, which is repeated until the value of \(b_{LoA}\) is greater or equal than the value of \(b_{k+1}^{next}\), the calculation takes as many times as the random variable \(x\) is greater or equal to the value \(k\), which is the _sequence number_ of the particular transmission/procession. When the loop function ends, the particular video/image starts to be transmitted/processed to the client. Due to the requirement for a rapid response to the client's request, the proposed algorithm's process is predicted to take less than one minute. The input of Algorithm 2 is based on three values that are necessary for the operation of the algorithm; first, the value of the _packet loss rate_ (\(PL\)) count on the _sequence number_ (\(k\)) of each round; second, the value of the _round trip time_ count on the _sequence number_ (\(k\)) of each round; and third, the value of the _signal-to-interference and noise ratio_ count on the _sequence number_ (\(k\)) of each round. Additionally, as an input, Algorithm 2 obtains any additional information added from each user of the system. On the other hand, the output of Algorithm 2 extracts the transmission data of the video/image transmitted each time through the system. The proposed algorithm is evaluated through a Digital Twin scenario, simulating virtual Cloud-Servers and a Smart Hospital installation in which data produced from amonitoring system is transferred, managed, and processed [73; 74; 75; 76]. For the Digital Twin scenario, we used CloudSim and Cooja Contiki to simulate our proposed system and algorithm. We tested several scenarios on CloudSim to see how computationally complex the suggested approach is. The amount of time and data used in each situation varies. As we could see from the experimental findings in the next Section, our concept was evaluated for a various period of time and for a variety of energy consumption situations that employed and generated data.