The thesis work majorly focuses on the development methodologies of the Internet of Things (IoT). A detailed literature survey is presented for the discussion of various challenges in the development of software and design and deployment of hardware. The thesis work deals with the efficient development methodologies for the deployment of IoT system. Efficient hardware and software development reduces the risk of the system bugs and faults. The optimal placement of the IoT devices is the major challenge for the monitoring application. A Qualitative Spatial Reasoning (QSR) and Qualitative Temporal Reasoning (QTR) methodologies are proposed to build software systems. The proposed hybrid methodology includes the features of QSR, QTR, and traditional databased methodologies. The hybrid methodology is proposed to build the software systems and direct them to the specific goal of obtaining outputs inherent to the process. The hybrid methodology includes the support of tools and is detailed, i
This paper deals with a review-based study on the efficient development methodologies for the deployment of IoT systems. Efficient hardware and software development reduces the risk of system bugs and faults. However, the optimal placement of the IoT devices is one of the major challenges for the monitoring applications. In this paper, a combined Qualitative Spatial Reasoning (QSR) and Qualitative Temporal Reasoning (QTR) methodology is proposed to build IoT software systems. The proposed hybrid methodology includes the features of QSR, QTR, and traditional data-oriented methodologies. This methodology directs software systems to the specific goal in obtaining outputs inherent to the process. The hybrid methodology includes the support of tools integrated, and also fits the general purpose. This methodology repeats the structure of spatio-temporal reasoning. Segmentation and object detection are used for the division of the region into sub-regions. Furthermore, the coverage and connect