http://www.warse.org/IJETER/static/pdf/file/ijeter237892020.pdf

Abstract

Wireless Sensor Network is one of the most rapidly developing technologies with a wide range of applications which includes a sensing process, security providence and surveillance, environmental sensing and military applications. Significant trend led to the emergence of small and low-cost computation and communication devices, called sensor nodes. Sensors are capable of sensing and transmitting process by consuming some amount of energy. The devices have the potential to serve as a catalyst for major changes. FEEM (Fuzzified Energy Efficient Mechanism) is a clustering based protocol proposed for continuous data-gathering with reduced energy consumption in WSN. The network is organized into clusters with cluster-heads periodically collecting, aggregating/compressing the data from nodes within the cluster, before sending them from Cluster head to Base station. Cluster-heads are changed periodically based on the Residual Energy available with the nodes in the cluster. The protocol is built based on the existing LEACH protocol to increase the lifetime of sensor network as well as to provide the energy efficiency at each node in WSN.

Evolution of the Testing Strategies using Advanced Automation and Artificial Intelligence in Software Development

“…For every new build sanity test job will be automatically triggered into integrated tools like Jenkins and based on sanity results QA teams will decide whether to accept or reject the build. Once the build is accepted, QA teams will test the deployed stories and report the bugs in version and will be tracked till closure [26]. Version tool will be used for logging and tracking the defects rose as part of functional testing and tracked to closure.…”

“…The tools will be implemented by the engineers for addressing the problem. Many AI applications are extremely difficult and time-consuming to build and it requires vigilant analysis, modeling, system design, engineering, test, and evaluation [2]. The skills in software engineering help to build successful AI systems.…”