Automated Livestock Practices: Incorporation Emerging Contemporary Technologies Toward Sustainable Livestock in Era of Smart Cities

Currently, numerous spheres now face a wider range of needs due to the increasingly competitive and globalized global market. Moreover, digital technologies are necessary for analysis and comprehension in many sectors of contemporary society. For instance, Internet of Things (IoT) has the potential to revolutionize livestock management, including the dairy cattle industry, by providing real-time data and enabling data-driven decisions to improve animal welfare, increase productivity, and promote sustainable farming practices. The main components of IoT-enabled livestock management include sensors, communication systems, data storage, and analysis systems. These components of IoT-enabled livestock management improve animal welfare, increase productivity, and reduce environmental impact. As well as promoting sustainable farming practices through using of precision farming methods, early illness detection, prevention, and improved animal reproduction and breeding.  Given the importance of leveraging IoT in livestock, this study examines and categorizes IoTs’ applications based on their functionalities and objectives. Thus, this process has been conducted by identifying criteria or factors that are important for evaluating the effectiveness of IoT applications. To serve the study’s objectives, we are harnessing various techniques. Firstly, we are modeling the identified IoTs applications’ criteria into levels that encompass a set of nodes by utilizing Tree Soft Technique (TrST). Secondly, Multi-Criteria Decision Making (MCDM) techniques are utilized for certain roles as criteria importance through inter-criteria correlation (CRITIC) for analyzing identified criteria and determining weights for them. These weights are leveraged in another technique of MCDM in this study for ranking IoT applications entailed in TOmada de Decisao Interativa Multicriterio (TODIM). The utilized techniques operate within the sovereignty of neutrosophic theory for supporting these techniques in uncertain situations and when treated with incomplete data.