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| Title | Next-Generation Iot Use Cases Across Industry Verticals Using Machine Learning Algorithms |
|---|---|
| ID_Doc | 39234 |
| Authors | Kalaiarasan T.R.; Anand S.; Anandkumar V.; Ratheeshkumar A.M. |
| Year | 2021 |
| Published | Applied Learning Algorithms for Intelligent IoT |
| DOI | http://dx.doi.org/10.1201/9781003119838-3 |
| Abstract | Internet of Things is an interconnection of objects or things through the internet and enables exchange of data where every object is provided a unique identifier and the data are transferred through the network. All the devices can be connected to a network and controlled at our fingertips using web-based applications or mobile applications. This technology fosters the growth of the internet and reduces human intervention, thereby making life very easy. Due to the transformation of agriculture to smart agriculture, cities to smart cities, payments to smart payments, IoT plays a major role in all the fields prevalent in today’s society. It is also predicted that in the coming years, the number of devices and applications that are connected will exponentially increase. With the rapid growth and a busy world, it is necessary that this kind of technology would be able to drive us and control everything at our own comfort. It has greater advantages like optimization, decision-making, and improved business strategies for satisfying the customers. Industrial IoT is a subset of IoT, which takes the concept of IoT, is applied with business scenarios, and leads to increased efficiency and greater savings. The market is highly benefited with the capability to monitor the machines remotely and monitor environmental conditions. It is not limited to specific domains; it plays a pivotal role in the field of health care by enabling patients and medical practitioners to communicate regularly in terms of the treatment, medications, and so on. This chapter is focused on the industrial use cases, which are elaborated below: Machine diagnosis systems detect faults in the machines, and also monitor the operating conditions. The performance of the machine is analyzed by comparing it with normal operating conditions. Inventory management system is used to monitor the inventor and maintain inventory level using RFID tags. Monitor the environmental conditions inside the industry by identifying toxic gases using various gas sensors, based on which hazardous zones can be identified. Hence, remedial measures can be taken by providing proper ventilation. Monitor the noise level in industry using noise monitoring stations. Noise maps are generated based on collected data. Devices in the form of wearables make remote monitoring of patients in the healthcare sector easy. © 2022 Taylor & Francis Group, LLC. |
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