## 1 Introduction
[8] also studies in their review about factors role in wound healing and they found that any technique which can measure O\({}_{2}\) help to patients who going through hyperbaric oxygen therapy to confirm oxygen presence in blood which is necessary for fast wound recovery [9]. * Exterior environment pollutants may contain bacteria and microbes which may cause infection, which may turn acute wound to chronic wound. * Smoke in exterior environment contains toxic elements e.g., nicotine, carbon monoxide, and hydrogen cyanide. These toxics components e.g., Nicotine causes reduction in nutritional blood flow to the skin, which results in tissue ischemia and impaired healing of injured tissue. Moreover, nicotine also cause reduction in proliferation of red blood cells, fibroblasts, and macrophages. Another smoke components i.e., Carbon monoxide lessens oxygen transport and metabolism. Clinically, it has been observed that smokers with wounds resulting from trauma, disease, or surgical procedures showed slower healing rate [10]. Although previous clinical research showed effect of wet and dry environment on wound healing which provided a base for wound monitoring systems, but with comprehensive previous studies as showed in Table 1 we determined three given stimuluses to design an effective wound monitoring system. 1 Previous Studies focused on investigation of dry and wet environment influence on wound healing. 2 Previous studies of wound healing considered just one environmental factor at a time e.g., Moisture, temperature, oxygen, pH etc. 3 Previous Studies only used one sensor to monitor wound healing i.e., biosensor for uric acid detection. 4 Expensive sensors arrays are mostly used previously in healthcare applications. 5 Intelligent decision making approaches were not used in previous studies e.g., neural network to examine exterior microenvironment for wound healing. In this paper, we proposed a smart wound care approach based on Exterior environment monitoring System designed by using Arduino UNO microcontroller (Arduino, Somerville, TX, USA) in combination with multi sensors to read exterior environment and then integrated it with MATLAB (The MathWorks, Natick, MA, USA, 2017) for analysis. MATLAB use NN model to investigate real time exterior environment in to continuous or impaired healing class. Experiments showed that EEMS (External Environment Monitoring System) read and record current exterior environment values which can further correctly classify by Neural Network in MATLAB. The proposed approach provides a solution of mentioned four key issues in a robust manner. The four major concerns addressed by the proposed approach discussed below. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Work Year** & **Sensor/Technique Use** & **Purpose** \\ \hline
[11] 2007 & Sensors array & Moisture level monitoring \\
[12] 2010 & Gas sensor array & infection detection of wound \\
[13] 2014 & Wireless biosensors & Monitoring application for healthcare \\
[14] 2015 & Web server and android & Health monitoring \\
[15] 2015 & RFID (Radio Frequency ID) Epidermal Sensor & Wound Monitoring and Healing \\
[16] 2016 & pH sensor array & pH level Detection for wound \\
[17] 2018 & Uric acid Biosensor & monitor wound healing \\
[18] 2019 & convolutional neural network & Lung Disease Identification \\
[19] 2019 & Multilayer Neural Network & Land Environment monitoring \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Features of Previously Presented Wound Care Techniques. * The proposed approach identifies real time environment feasibility for wound healing process two classes i.e., first one indicates continuous healing and second indicate impaired healing. * The proposed approach checks environment feasibility by dealing with multiple environment constituents at a time i.e., temperature, humidity, air quality and dust particles. * Our proposed approach used three sensors: a temperature and humidity sensor, a gas sensor and air quality sensor to sense current environment in more efficient manner.