Healthcare and medical advances have prolonged human life and thus have led to increasing numbers of elderly individuals. To make their lives more convenient, several ubiquitous technologies have been considered, including the RFID system, which can play a vital role in elderly care by caregivers as well as by elderly individuals themselves. Caregivers can take advantage of the RFID system by recording and tracking elderly individuals' belongings and assisting these individuals in healthcare provision by accessing their relevant information, among others. Similarly, the RFID system can help manage elderly individuals' daily lives by reminding them of their daily schedules (e.g., reminding them to take medicine on time) and tracking their personal belongings, among others. In addition, the RFID system can mitigate human errors such as medical mistakes, delays in service provision, and hassles in tracking and identifying patients and objects. This study provides a survey of solutions proposed in the literature and discusses the potential benefits of integrating the RFID system with sensors and applying the integrated system. In addition, the study addresses the opportunities, technological challenges, and research directions for the integrated RFID system in the context of smart solutions in elderly care facilities.

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We present a decentralized medium access control protocol for cognitive radio wireless sensor networks. The proposed protocol allows secondary wireless sensors nodes to recognize spectrum opportunities and transmits data based on the licensed users' arrival prediction on the channel. It estimates the number of active cognitive wireless sensor nodes and it also adjusts the sleep cycle in order to conserve energy. The proposed protocol does not need a dedicated common control channel to negotiate for the data channels. We evaluate delay, energy consumption, and goodput, which are the three important qualities of service parameters through simulation. The simulation results show that the proposed approach achieves higher energy conservation with a small cost of delay and adequate aggregated goodput.

In this study, we consider a perishable inventory system that has an (s, Q) ordering policy, along with a finite waiting hall. The single server, which provides an item to the customer after completing the required service performance for that item, only begins serving after N customers have arrived. Impatient demand is assumed in that the customers waiting to be served lose patience and leave the system if the server’s idle time overextends or if the arriving customers find the system to be full and will not enter the system. This article analyzes the impatient demands caused by the N-policy server to an inventory system. In the steadystate, we obtain the joint probability distribution of the level of inventory and the number of customers in the system. We analyze some measures of system performance and get the total expected cost rate in the steadystate. We present a beneficial cost function and confer the numerical illustration that describes the impact of impatient customers caused by N-policy on the inventory system’s total expected cost rate.

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Present-day queuing inventory systems (QIS) do not utilize two multi-server service channels. We proposed two multi-server service channels referred to as T1S (Type 1 n-identical multi-server) and T2S (Type 2 m-identical multi-server). It includes an optional interconnected service connection between T1S and T2S, which has a finite queue of size N. An arriving customer either uses the inventory (basic service or main service) for their demand, whom we call T1, or simply uses the service only, whom we call T2. Customer T1 will utilize the server T1S, while customer T2 will utilize the server T2S, and T1 can also get the second optional service after completing their main service. If there is a free server with a positive inventory, there is a chance that T1 customers may go to an infinite orbit whenever they find that either all the servers are busy or no sufficient stock. The orbital customer can request for T1S service under the classical retrial policy. Q(=S−s) items are replaced into the inventory whenever it falls into the reorder level s such that the inequality always holds n<s. We use the standard (s,Q) ordering policy to replace items into the inventory. By varying S and s, we investigate to find the optimal cost value using stationary probability vector ϕ. We used the Neuts Matrix geometric approach to derive the stability condition and steady-state analysis with R-matrix to find ϕ. Then, we perform the waiting time analysis for both T1 and T2 customers using Laplace transform technique. Further, we computed the necessary system characteristics and presented sufficient numerical results.

In response to the digital revolution, nowadays, many companies operate online and offline businesses in parallel to ensure their future competitiveness. This research examines the inventory strategy for multi-product vendor-buyer supply chain systems, considering space constraints and carbon emissions, in order to improve competence in managing online and offline integrated orders. We amalgamate costs and emissions in transport and storage. Here, we divide the warehouse of the buyer into two stages: one for satisfying online orders and the other for satisfying offline orders. We also assume that additional crashing costs reduce the lead times for receiving products in the buyer’s warehouse. This study demonstrates a mathematical model in the form of a constrained non-linear programme (NLP) and derives a Lagrangian multiplier method to solve it. An iterative solution procedure is designed in order to attain sustainable manufacturing decisions, which are illustrated numerically.