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A location-aware service (LAS) is an imperative topic in ambient intelligence; an LAS recommends suitable utilities to a user based on the user's location and context. However, current LASs have several problems, and most of these services do not last. This study proposes an optimization-based approach for enhancing the sustainability of an LAS. In...
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... 5 illustrates a summary of applicable methods in this field. Table 2 shows a summary of the advantages and disadvantages of these methods, which motivated the combination of multiple optimization methods in this study. Figure 6 shows an example in which a user travels from S (the current location) to D (destination). ...
Citations
... Location-Aware Systems (LASs) [15], [16] are computing systems that detect and utilize location data to deliver useful information, services, or actions relevant to the geographical position of an individual or an object when they enter a vicinity area. These systems rely on positioning technologies, such as GPS, Wi-Fi, BLE, and RFID to accurately determine the location of a user or an object. ...
The pervasiveness of mobile computing has become ubiquitous in daily life, particularly for people who visit various locations in the physical world through their mobile devices. Similarly, providing valuable services, actions, and information tailored to a specific area or environment can make user interactions more seamless , personalized, and convenient. The article proposes an intelligent location-aware architecture for mobile computing environments that interacts with individual mobile users by automatically providing local services, helpful information, and personalized recommendations based on their current location and user context. Experimental results show that the proposed architecture is intelligent, privacy-preserving, scalable, reliable, and can be efficiently deployed in various real-world environments.
... Location-Aware Systems (LASs) [15], [16] are computing systems that detect and utilize location data to deliver useful information, services, or actions relevant to the geographical position of an individual or an object when they enter a vicinity area. These systems rely on positioning technologies, such as GPS, Wi-Fi, BLE, and RFID to accurately determine the location of a user or an object. ...
Mobile devices have become ubiquitous in daily lives, especially for people who use their smartphones throughout the day while visiting different places in the real world. Providing valuable services and information that are tailored to a specific area or environment can make user interactions more seamless, personalized, and convenient. This paper proposes an intelligent location-aware architecture for mobile computing environments that interacts with individual mobile users by automatically providing appropriate local services, information, and personalized recommendations based on their current location and profiles while tracking their position and movement. Experimental results show that the proposed architecture is intelligent, scalable, reliable, and can be efficiently deployed in various real-world environments.
... For faster convergence, heuristic methods can be hybridised with meta-heuristic approaches and employed effectively for online applications. Heuristic algorithm solutions, however, might not be the best options and be challenging to apply to new circumstances (Tsai & Chen, 2014). ...
The distribution system is the largest segment of the electrical power system and the final stage in delivering electricity to consumers. It experiences power losses which could be technical or non-technical due to its radial configuration and connected components. Technical losses occur as energy dissipation in the form of heat in the system components, which is unavoidable. It affects the efficiency of the system and increases operational costs. Therefore, the reduction is essential for adequate power supply and improvement in utility revenue generation. This study focuses on reducing power losses on 11 kV Taiwo distribution feeder in Ilorin using the Network reconfiguration approach. The feeder was modelled, and its power losses were evaluated based on the Backward Forward Sweep method suitable for the radial network. The reconfigured network was optimised using the Particle Swarm Optimisation technique. The study shows that the values of feeder real power losses before and after reconfiguration are 176.883 kW and 121.972 kW, respectively.Further improvement was, however, achieved when PSO was used for the reconfiguration, as the power loss value stands at 98.465 kW. This is 44.33 % reduction compared to the initial power loss value and 19.273 % after reconfiguration. Furthermore, the values of the reactive power losses before and after reconfiguration are 9.474 kVar and 6.527 kVar, respectively, amounting to a 31.11 % reduction. However, PSO reduces the value to 3.101 kVar, which is 67.27 % of the initial value. Thus, radial distribution network reconfiguration using PSO has proven to be a robust method for reducing power loss in the distribution network.
... The analytical modelling for optimization is complicated compared to the numerical one. Table 5 summarizes the advantages and disadvantages of different optimization techniques [56]. In this paper, the optimization procedure was conducted using the Optimization COMSOL module (BOBYQA solver) which is appropriate for the piezoelectric energy harvesting problem and gives the maximum power compared to comparable algorithms (Heuristics Genetic Algorithm) [12]. ...
... Advantages and disadvantages of different optimization techniques[56]. ...
Previous broadband energy harvester techniques met many challenges like output power with a sharp peak, small enhancement in bandwidth, and large dimensions and weights. This paper introduces the Automatic Resonance Tuning (ART) technique of two piezoelectric beams to manage these challenges. The energy harvester of two clamped beams automatically adapts their natural frequencies corresponding to the ambient vibration using (sliding masses over the beams). The optimization using COMSOL was conducted to determine the frequency ranges of the low-frequency beam and high-frequency beam and maximize the output power. The bandwidth of the optimized ART harvester is broadened from 27 to 137Hz, ultra-broad bandwidth (110Hz). Our Finite Element Method (FEM) results were validated with experimental results that exhibited excellent convergence. Usually, the dataset of voltage and power is collected by the FEM. Voltages and power evaluated using FEM for some positions are used as the convolutional neural network (CNN) input. CNN predicts the most of masses' positions over the harvester due to the complexity of repetition implementation FEM in several positions. Then, the CNNs are trained for new wide masses position prediction. The mean square error (MSE) of the training dataset is 2.5601×10-7μw and the performance of the CNN training is 97.62% accuracy (P%), 95.38% regression rate (R%), and 93.78% F-score (F%), at epoch 1000, which shows the effectiveness of the proposed approach.
... To facilitate the optimization of NLP model I, it must be converted into a more tractable model (Tsai and Chen 2013;Lin et al. 2018;Hübner et al. 2020;Wang et al. 2020). The objective function involving square roots should first be replaced with the following linear and quadratic equations (Tsai and Chen 2014): ...
A decision maker usually holds various viewpoints regarding the priorities of criteria, which complicates the decision making process. To overcome this concern, in this study, a diversified AHP-tree approach was proposed. In the proposed diversified AHP-tree approach, the judgement matrix of a decision maker is decomposed into several subjudgement matrices, which are more consistent than the original judgement matrix and represent diverse viewpoints on the relative priorities of criteria. Thus, a nonlinear programming model was established and optimized, for which a genetic algorithm is designed. To assess the effectiveness of the proposed diversified AHP-tree approach, it was applied to a supplier selection problem. The experimental results showed that the application of the diversified AHP-tree approach enabled the selection of multiple diversified suppliers from a single judgement matrix. Furthermore, all suppliers selected using the diversified AHP-tree approach were somewhat ideal.
... R 2 was found to be 0.87, which was sufficiently high to ensure that the collected data followed a learning process. Subsequently, the training data were used to build the MBQP model, which was solved using a branch-and-bound algorithm [47][48][49][50] on a personal computer with Intel core i7-7700 CPU @ 3.60 GHz and 8 GB RAM in 10 s. Moreover, was set to 0.2 so that an 80% inclusion interval was constructed. ...
Existing methods for forecasting the productivity of a factory are subject to a major drawback—the lower and upper bounds of productivity are usually determined by a few extreme cases, which unacceptably widens the productivity range. To address this drawback, an interval fuzzy number (IFN)-based mixed binary quadratic programming (MBQP)–ordered weighted average (OWA) approach is proposed in this study for modeling an uncertain productivity learning process. In the proposed methodology, the productivity range is divided into the inner and outer sections, which correspond to the lower and upper membership functions of an IFN-based fuzzy productivity forecast, respectively. In this manner, all actual values are included in the outer section, whereas most of the values are included within the inner section to fulfill different managerial purposes. According to the percentages of outlier cases, a suitable forecasting strategy can be selected. To derive the values of parameters in the IFN-based fuzzy productivity learning model, an MBQP model is proposed and optimized. Subsequently, according to the selected forecasting strategy, the OWA method is applied to defuzzify a fuzzy productivity forecast. The proposed methodology has been applied to the real case of a dynamic random access memory factory to evaluate its effectiveness. The experimental results indicate that the proposed methodology was superior to several existing methods, especially in terms of mean absolute error, mean absolute percentage error, and root mean square error in evaluating the forecasting accuracy. The forecasting precision achieved using the proposed methodology was also satisfactory.
... Heuristics are more easily programmed, and can determine a near-optimal solution. However, in some cases, the results may be far from optimal solution and adaptation to new situations is difficult [18]. Also, in water allocation issues where the complexities of the system are high and the system involves a large number of physical components as well as resource supply priorities and consumer demand priorities, the use of optimization models alone faces difficulties. ...
Severe water scarcity in recent years has magnified the economic, social, and environmental significance of water stress globally, making optimal planning in water resources necessary for sustainable socioeconomic development. One of the regions that is most affected by this is the Sistan region and its Hamoun wetland, located in southeast Iran. Water policies are essential to sustain current basin ecosystem services, maintaining a balance between conflicting demands from agriculture and the protection of wetland ecosystems. In the present study, a multi-objective optimization model is linked with the Water Evaluation and Planning (WEAP) software to optimize water allocation decisions over multiple years. We formulate and parameterize a multi-objective optimization problem where the net economic benefit from agriculture and the supply of environmental requirements were maximized, to analyze the trade-off between different stakeholders. This problem is modeled and solved for the study area with detailed agricultural, socioeconomic , and environmental data for 30 years and quantification of ecosystem services. By plotting Pareto sets, we investigate the trade-offs between the two conflicting objectives and evaluate a possible compromise. The results are analyzed by comparing purely economic versus multi-objective scenarios on the Pareto front. Finally, the disadvantages and advantages of these scenarios are also qualitatively described to help the decision process for water resources managers.
... A new type of mobile technology, known as indoor positioning technology systems (IPS), enables the collection of massive human-tracking data in indoor settings. Recently, researchers have begun recognizing the value of indoor location data analysis [20][21][22][23][24]. An IPS is a technology employed to locate objects or people in a building through radio waves, magnetic fields, acoustic signals or other sensory information using mobile devices [25]. ...
Retailers need accurate movement pattern analysis of human-tracking data to maximize the space performance of their stores and to improve the sustainability of their business. However, researchers struggle to precisely measure customers’ movement patterns and their relationships with sales. In this research, we adopt indoor positioning technology, including wireless sensor devices and fingerprinting techniques, to track customers’ movement patterns in a fashion retail store over four months. Specifically, we conducted three field experiments in three different timeframes. In each experiment, we rearranged one element of the visual merchandising display (VMD) to track and compare customer movement patterns before and after the rearrangement. For the analysis, we connected customers’ discrete location data to identify meaningful patterns in customers’ movements. We also used customers’ location and time information to match identified movement pattern data with sales data. After classifying individuals’ movements by time and sequences, we found that stay time in a particular zone had a greater impact on sales than the total stay time in the store. These results challenge previous findings in the literature that suggest that the longer customers stayed in a store, the more they purchase. Further, the results confirmed that effective store rearrangement could change not only customer movement patterns but also overall sales of store zones. This research can be a foundation for various practical applications of tracking data technologies.
... In a smart hospital, wireless sensors are attached to mobile patients to collect real-time information such as their pulses and oxygen saturation readings [17]. The location of a patient with a smart phone can be detected by comparing the WiFi signal strengths in different zones [43]. ...
Smart technologies present numerous opportunities for enhancing mobile health care. However, existing applications of smart technologies to mobile health care face several difficulties. As a result, whether a smart technology application to mobile health care will be sustainable is questionable. To address this issue, the fuzzy geometric mean (FGM)–α-cut operations (ACO)–fuzzy weighted average (FWA) approach is proposed in this study. In the proposed methodology, at first FGM is applied to aggregate multiple experts’ opinions on the relative importance of a critical factor. Then, ACO is applied to derive the absolute fuzzy importance level of the critical factor. At last, FWA is applied to assess the sustainability of the smart technology application to mobile health care. The proposed methodology has been applied to assess the sustainability of thirteen smart technology applications to mobile health care. According to the experimental results, the most and least sustainable smart technology applications to mobile health care were smart mobile service and smart clothes, respectively. In addition, the ranking result using the proposed methodology was somewhat different from those using existing methods based on approximation.
... According to Zheng et al. (2010), mobile recommendation refers to making timely and targeted recommendations for users about places they might be interested to visit and activities they would like to engage in. To this end, location-sensing technologies such as global positioning systems (GPSs) are applied to detect a user's location (Tsai and Chen 2014). A client-side app is then provided for a user to input his or her requirements for the mobile recommendation. ...
The existing mobile hotel recommendation systems are usually subject to a difficult problem—travelers choose dominated hotels. This problem is difficult to resolve because there is no reason to recommend a hotel that is inferior to another in all aspects. To address this problem, an artificial dimension is added to each hotel to model unknown personal preferences. The possible values along the artificial dimension and the weight associated with it are derived by solving an integer nonlinear programming problem. Thus, the proposed methodology hybridizes objective and subjective weights. An illustrative example is provided to show the applicability of the proposed methodology. In addition, a field study was conducted in a small region of Seatwen District, Taichung City, Taiwan to evaluate the possible advantages of the proposed methodology over existing methods. The experimental results showed that the proposed methodology outperformed five existing methods in improving the successful recommendation rate, with the most significant advantage being up to 33 %. Furthermore, the recommendation results generated using the proposed methodology were found to be less risky.
