Designing Smart Control Systems Based on Internet of Things and Big Data Analytics

Khan, Murad; Han, Kijun; Karthik, S.

doi:10.1007/s11277-018-5336-y

Cited by 47 publications

(19 citation statements)

References 29 publications

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“…The future smart home will be consisting of many sensors controlling various activities ranging from security to maintaining a fair usage of energy [11,12,13]. The human behavior and interaction with smart home appliances changes rapidly and, therefore, relying on a fixed model for scheduling household appliances is difficult.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Scheduling of Operational Time for Smart Home Appliances Based on Reinforcement Learning

2020

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The scheduling of the operational time of household appliances requires several parameters to be tuned according to the available energy supplied to a smart home. However, scheduling of operational time of multiple appliances in a smart home itself is the NP-hard problem and thus requires an intelligent, heuristic method to be solved in polynomial time. In this research work, we propose Real-time Scheduling of Operational Time of Household Appliances based on the well-known value iterative reinforcement learning called Quality learning (RSOTHA-QL). The proposed RSOTHA-QL scheme operates in two phases. In the first phase, the agents of the Q learning act by interacting with the smart home environment and obtain a reward. The reward value is further utilized to schedule the operational time of household appliances in the next state ensuring minimum energy consumption. In the second phase, the dissatisfaction arises due to scheduling of operational time of the household appliances of the home user is maintained by categorizing the household appliances into three groups: 1) deferrable, 2) non-deferrable, and 3) controllable. Besides, using the shared memory synchronization phenomenon, the agents attached to each appliance of the smart home become coordinated. The simulation and experiments are performed in a smart home scenario comprised of a single user and multiple appliances. As compared with our previous research work using the Least Slack Time (LST) scheduling algorithm and scheduling based on demand-response strategy, it is revealed that the operational time of the household appliances is efficiently scheduled to reduce the energy consumption and dissatisfaction level of the home users significantly.

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Section: Related Workmentioning

confidence: 99%

Real-Time Scheduling of Operational Time for Smart Home Appliances Based on Reinforcement Learning

2020

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“…IoT, with help of futuristic protocol and algorithms, became a major contributor to global communication. It connects a large number of devices, wireless sensors, home appliances, and electronic devices to the Internet [ 4 ]. The application of IoT can be found in the field of agriculture [ 5 ], automobiles [ 6 , 7 ], home [ 8 ], and healthcare [ 1 , 9 ].…”

Section: Introductionmentioning

confidence: 99%

IoT-Based Applications in Healthcare Devices

Pradhan

Bhattacharyya

Pal

2021

Journal of Healthcare Engineering

261

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The last decade has witnessed extensive research in the field of healthcare services and their technological upgradation. To be more specific, the Internet of Things (IoT) has shown potential application in connecting various medical devices, sensors, and healthcare professionals to provide quality medical services in a remote location. This has improved patient safety, reduced healthcare costs, enhanced the accessibility of healthcare services, and increased operational efficiency in the healthcare industry. The current study gives an up-to-date summary of the potential healthcare applications of IoT- (HIoT-) based technologies. Herein, the advancement of the application of the HIoT has been reported from the perspective of enabling technologies, healthcare services, and applications in solving various healthcare issues. Moreover, potential challenges and issues in the HIoT system are also discussed. In sum, the current study provides a comprehensive source of information regarding the different fields of application of HIoT intending to help future researchers, who have the interest to work and make advancements in the field to gain insight into the topic.

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“…Heterogeneous technologies of specialized protocols and algorithms have been steadily developed by IoT. The IoT plays a vital role in the global connectivity between millions of wired and wireless sensor systems, electronic devices such as TVs, refrigerators, etc., linked to the Internet [3]. In several sectors, such as agriculture [4,5] , healthcare [6], entertainment [7], automotive [8], sports, home [9,10], industrial appliances, business [11], etc., it then plays an enormous position.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Healthcare Systems using Internet of Things

Ramesh

Sekar

2021

ITM Web Conf.

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The Internet of Things allows things to become active users, facilitating interaction with things and the sharing of data between them. The most interesting issue in the science world, the public sector and industry in the IoT is unavoidable. It ensures a seamless relationship between doctors and patients that results in medical treatment with high quality results. This is accomplished by constant surveillance of patients through the use of sensors. The collected data is registered for potential uses and used for analytics. The analytical approach offers the opportunity for disease detection in healthcare results. This paper concerns the Internet of Things in healthcare and explores the different algorithms used in it. The system involved in analytics of healthcare and data sources involved in analytics are further clarified. Finally this paper demonstrates the Internet of Things and Big Data survey of healthcare systems with a reference table.

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Designing Smart Control Systems Based on Internet of Things and Big Data Analytics

Cited by 47 publications

References 29 publications

Real-Time Scheduling of Operational Time for Smart Home Appliances Based on Reinforcement Learning

Real-Time Scheduling of Operational Time for Smart Home Appliances Based on Reinforcement Learning

IoT-Based Applications in Healthcare Devices

A Survey on Healthcare Systems using Internet of Things

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