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The impact of natural disasters on human life, the environment and the flora and fauna can be contained to large extent by intelligent human intervention. This study introduces the human capabilities which can be extended considerably with technology. Internet of things have always provided opportunities for predicting and managing manmade/natural disasters. The extreme reason for causing soil erosions, landslides, cloud bursts, floods, etc., are due to excessive rainfall. However, the flood is one of the most happening natural disasters, following Bihar to be the most affected region due to floods. Lots of lives and properties were lost and damaged.

This implemented researchers to introduce an advanced solution for such calamities. Expectations were developed that it would signalize authority as early as possible so that advanced measures are taken before the effect. The lack of sensing or alarming technology in India pushed researchers to develop a model using the Android app that basically detected the upcoming flood and other calamities.

Most importantly the entire model was programmed with IoT and its techniques so that the response is quicker and more accurate.

This research study is original.

The study aims to develop recommendations for optimal Internet of things (IoT) based solutions for a smart precision irrigation automation platform using morphological thinking (MT). The smart irrigation system (SIS) can be applied for green roof and green wall (GRGW) design by studying the relationships and configurations that will be analyzed, listed and synthesized, representing “solutions spaces” and their possibilities.

The research examines studying various cases of SIS; and assessing and analyzing the identified case studies through a decision support system (DSS) considering several factors regarding IoT, plant characteristics, monitoring, irrigation system and schedule, climate, cost and sensors used.

To develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform.

The research paper analyzes and proposes a simultaneous solution to two conflicting problems. On the one hand, the paper proposes to apply greening of walls and roofs in hot arid regions, which will achieve greater environmental comfort. However, this is extremely difficult to implement in hot arid regions, since there is an objective problem – a lack of water. At the same time, the paper proposes the most rational approaches to organizing an irrigation system with the lowest water consumption and the highest efficiency for landscaping. Accordingly, this paper focuses on evaluating different types of SIS about the hot-arid climate in Qatar. The study aims to develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform, which can be applied for green wall and roof design.

The mechanical facilities of large-scale buildings have many complexities, so facility management (FM) encounters a massive amount of information during the operation, and inspection is not implemented efficiently. This study aims to integrate building information modeling (BIM), augmented reality (AR) and sensors to mitigate the operation and maintenance (O&M) problems of mechanical facilities by establishing intelligent management.

The component-level data of an under-construction commercial complex were implemented in a 3D model in Autodesk Revit and Navisworks. Then, sensors were installed in mechanical facilities to provide vital online information for the model. Moreover, Unity was used on Vuforia for the AR visualization of the devices.

It was found that FM not only could obtain building information but can also visualize the functioning of mechanical facilities online through a 3D model in BIM. Thus, in the case of a failure, the AR platform is used on tablets, smartphones and smart glasses to show the technician how mechanical facilities can be repaired and maintained.

Previous studies focused on some factors and processes to improve mechanical FM and did not cover the entire aspect. However, this method reduces the average maintenance time, extends the lives of mechanical devices and prevents unpredicted failures.