Proposing a Density-Based Clustering Approach (DBCA) to Aggregate Data Collected from the Environment in Arid Area for Desertification

Table 1

Summarization of related works reviewed in this research.

Related	Author name	Year	Brief explanation
Proposed algorithm based on PSO	Edla et al. [16]	2019	Proposed a clustering algorithm based on particle swarm optimization and a new fit function taking into account the average distance of clusters, gate load, and number of overhead gates in the network suggested.
	Wang et al. [23]	2018	Proposed a new algorithm to optimize the performance of the PSO algorithm. In the proposed algorithm, the nodes are first randomly placed in fixed geographical areas. Then, a network is created between these nodes. The whole network is then divided into several subnetworks, and the amount of coverage and energy consumption for each subnetwork is calculated.
Survey	Mahdi et al. [17]	2016	First briefly reviewed the various clustering methods and then they reviewed the node clustering methods that have been proposed by several researchers for tracking targets in wireless sensor networks and are based on data aggregation. They explained and briefly stated the advantages and disadvantages of each one of these methods.
	Ali et al. [21]	2018	Categorized all research conducted by other researchers based on important parameters such as their objectives, applications, communication technology, types of data sets used, discovery, and types of data. In addition, several case studies were examined to demonstrate the role of sensor clouds in providing high computational capabilities. In addition, they outlined some of the challenges of collecting data in sensor clouds.
	Ge et al. [24]	2018	Studied on the similarities and differences between the big data technologies used in different areas of the Internet of Things discussed and proposed a platform for mutual understanding of these differences and similarities and mentioned that some of these technologies can be used in several IoT domains. Finally, these researchers proposed a conceptual framework to guide other researchers in selecting Big Data technologies in various areas of the Internet of Things.
Proposed algorithm based on PEGASIS algorithm	Wang et al. [22]	2018	Proposed the advanced Power Efficient Gathering in Sensor Information Systems (EPEGASIS) algorithm to reduce the hot spot problem.
	Wang et al. [25]	2019	Proposed the combination of the PEGASIS algorithm and the Hamilton loop algorithm. Through a combination of single-hop and multihop mechanisms and a moving agent added a mobile agent node (MA), these authors proposed a design of an optimal empower Hamilton loop using a local optimization algorithm.
Reduce energy consumption	Mahdi et al. [19]	2016	Proposed a fully distributed algorithm named as Endocrine Inspired Sensor Activation Mechanism for Multi-Target Tracking (ESAM) in which node placement is self-organizing and energy efficient. The main purpose of the ESAM is to reduce energy consumption and increase network lifespan.
	Mahdi et al. [20]	2016	Proposed a routing strategy aimed at maximizing overlap paths for efficient data aggregation and linking cost issues in clustered WSNs, known as the weighted data aggregation protocol (WDARS). The main purpose of WDARS is to reduce energy consumption, increase network lifespan, increase production capacity, and package delivery ratio.