# Performance Analysis of IoT-Based Health and Environment WSN Deployment
## 3 Health and Environment Sensor Network Deployment
### GIS-Based WSN Deployment  
As the previous section shows, WSN deployment is one of the important problems in several environmental and health applications with optimizing conflict objectives (coverage and power consumption or lifetime). The aim of WSN deployment is to find the optimal locations of the sensors so that the network coverage and lifetime are maximized. In WSN deployment, GIS plays key role in modeling the sensors that are located in a specific location (\(x,y\)) using point geometry and managing the network of the sensors. In addition, spatial analysis of GIS helps to calculate total coverage of the sensors as well as the overlapped coverage in the given region. The locations of the sensors have great impact on the WSN coverage and energy consumption and even cost. If the locations of the sensors is such that they have the maximum distance from each other according to the sensing range (the points have uniform spatial distribution), the network coverage is maximum and the number of sensors is minimum for the WSN deployment. However, increasing the distance between the sensors  
Figure 1: The research methodology. increases energy consumption. To reduce energy consumption, it is necessary to keep the distance between the sensors as short as possible, which this issue increases the number of sensors and thus the cost. Therefore, the main issue of the WSN deployment is to find the optimal locations of the sensors by considering both the sensing and communication ranges. In addition, to find optimal locations, the connectivity constraint is very important so that the sensors that are not located in the communication range cannot be connected and to make a network. WSNs, as a specialized type of wireless sensor network (WSN) in geospatial spaces, are used for computing everywhere. A WSN is a collection of tiny battery-powered sensor nodes in which information generated by each sensor node is directly related to its location [71]. A WSN can be considered as connected undirected graph represented by \(G\) (\(V\), \(E\)), where \(V=\{v_{1},\ v_{2},\ v_{3}\dots,\ v_{n}\}\) is a finite set of vertices representing sensor nodes, and \(E=\{e_{1,2},\ e_{1,3},\ \dots,\ e_{i,j},\ \dots,\ e_{n-1,\ n}\}\) is the edges representing the connection links between sensor nodes [72]:  
WSN, a set of spatially distributed sensor nodes, is deployed in a geospatial space to detect and monitor different phenomena [73; 74; 75]. The robustness of WSN in collecting and transmitting data is affected by the sensor limitations including sensing range, communication, power supply, and computational capacities. In WSN deployment, as one of the fundamental and major steps of the design process, finding sensor positions are conducted with regard to reducing the effects of sensor limitations. Therefore, WSN deployment is inherently a multi-objective problem. Among the different objectives, coverage and lifetime of the network are two main important objectives for increasing the effectiveness of WSNs [16; 17]. These objectives are limited by the connectivity constraint that there should be at least one link between sensor nodes [76]. Each sensor has several properties including sensing range and communication range. The sensing range assumes a circle with radius \(R_{\text{s}}\) in which the sensor is able to sense all the points. The communication range is Euclidean distance \(R_{\text{c}}\) that two sensors are able to communicate with each other if their distance is less than or equal to their communication ranges [16]. These ranges are shown in Figure 2. Each edge has m attributes denoted by \(w_{i,j}=\left\{w_{i,i^{\prime}}^{1},\ w_{i,j^{\prime}}^{2},\ \dots,\ w_{i,j}^{m}\right\}\) to represent distance, transmitting energy and so on. In addition, the connectivity between two nodes (node \(i\) and \(j\)) is defined with \(x=x_{1,2},\ x_{1,3},\ \dots,\ x_{i,j},\ \dots,\ x_{n-1,\ n}\). The value of \(x_{i,j}\) is one if there is an edge (\(e_{i,j}\)) between the nodes and the edge is selected, otherwise zero.