Wireless Sensor Networks (WSNs) are generally deployed with low-cost devices that have low power consumption and small-size sensor nodes. They can be used in several monitoring and control applications such as; health, agriculture, and environment. With the advent of Industry 4.0 and Artificial Intelligence (AI), WSNs attracted many industrial applications and specific implementation scenarios. In general, the sensor nodes compromising of WSNs consume vast energy during tracking and monitoring. This poses a challenge especially since most of WSNs are battery-operated and have very limited energy sources. Therefore, it is important to optimize power consumption and prolong the lifetime of WSNs. Many protocols have been proposed with emphasis on data forwarding and routing. These protocols, however, have not been designed to address interference and transmissions issues, such as communication link instability and packet drops. In addition, a quiet substantial amount of energy would be consumed during transmission, which leads to a degradation in network performance. In this research, an effective solution is proposed based on Spiral Clustering Based on Selective Activation Protocol (SCSAP). The objective is to enhance energy consumption and improve network performance, which makes it a good candidate for several Industrial tailored WSNs. In this solution, the network nodes are classified into two types; super and normal. Super nodes have a significant power source and are utilized to construct clusters and act as Cluster Heads (CHs). They have pre-defined locations with an optimized number of nodes selected for the best coverage that is determined in the Stable Election Protocol (SEP). As a result, the power consumption is reduced in the dynamic formatting of clusters. Normal nodes, on the other hand, are static. They have limited power and are connected to the super nodes. Normal nodes operate in two modes; active and sleep. In the active mode, they send data to the CHs and the Time Division Multiple Access (TDMA) is used to guarantee that the transmitted data are correctly received by the other nodes and that the power consumption of re-transmission is largely reduced. The simulation results of SCSAP have shown a 40% enhancement of network lifetime over the Threshold-sensitive Stable Election Protocol (TSEP). They have also shown that SCASP’s remaining power has descended slower than the Low-energy Adaptive Clustering Hierarchy (LEACH) protocol.

无线传感器网络（WSN）通常部署在低成本设备上，这些设备具有低功耗和小尺寸传感器节点。它们可用于多种监视和控制应用，例如：健康、农业和环境。随着工业 4.0 和人工智能（AI）、WSNs 吸引了许多工业应用和具体的实施场景。一般来说，影响 WSN 的传感器节点在跟踪和监控过程中会消耗大量能量。这带来了挑战，特别是因为大多数 WSN 都是电池供电的并且能源非常有限。因此，优化功耗和延长无线传感器网络的寿命非常重要。已经提出了许多强调数据转发和路由的协议。然而，这些协议并未设计用于解决干扰和传输问题，例如通信链路不稳定和数据包丢失。此外，在传输过程中会消耗大量能量，从而导致网络性能下降。在这项研究中，基于选择性激活协议（SCSAP）的螺旋聚类提出了一种有效的解决方案。目标是提高能源消耗并提高网络性能，这使其成为几个工业定制 WSN 的良好候选者。在该方案中，网络节点分为两类；超级和正常。超级节点具有重要的电源，用于构建集群并充当集群头 (CH)。它们具有预定义的位置，并为稳定选举协议 (SEP) 中确定的最佳覆盖范围选择了优化的节点数量。结果，在簇的动态格式化中降低了功耗。另一方面，普通节点是静态的。它们的功率有限，并且连接到超级节点。普通节点以两种模式运行；活跃和睡眠。时分多址（TDMA）用于保证传输的数据被其他节点正确接收，并大大降低重传的功耗。SCSAP 的仿真结果表明，网络寿命比阈值敏感稳定选举协议 (TSEP) 提高了 40%。他们还表明，SCASP 的剩余功率下降得比低能量自适应聚类层次 (LEACH) 协议要慢。