When using a gas stove to cook, the food or oil in the pot or pan may catch fire because of an excessively high temperature. In addition, people may be uncertain as to whether they have turned off the gas stove before leaving home and therefore feel compelled to return home to check. To solve these problems, this study has developed a smart kitchen fire prevention system that possesses the following devices and functions. (1) Sensors are installed above the stove top. When they detect flames, high temperature, or a gas leak, they immediately activate the gas shutoff device to turn off the gas supply. (2) The alarm produces a loud sound and flashes to warn the residents. (3) The Line reporting system sends Line messages to notify the residents and the community management center, and the main entrance door is automatically unlocked to allow relevant personnel to enter the house to deal with the accident. (4) An Internet protocol camera is installed in the kitchen to enable the residents to monitor the gas stove on their mobile phones. If they find the gas stove is still turned on, they can activate the gas shutoff device to shut off the gas supply from their phones. The system developed in this study can effectively reduce the loss that results from a kitchen fire.

This paper addresses the challenge of moving objects in a mobile wireless sensor network, considering the deployment of a limited number of mobile wireless sensor nodes within a predetermined area to provide coverage for moving objects traveling on a predetermined trajectory. Because of the insufficient number and limited sensing range of mobile wireless sensors, the entire object’s trajectory cannot be covered by all deployed sensors. To address this problem and provide complete coverage, sensors must move from one point of the trajectory to another. The frequent movement quickly depletes the sensors’ batteries. Therefore, solving the moving object coverage problem requires an optimized movement repertoire where (1) the total moving distance is minimized and (2) the remaining energy is also as balanced as possible for mobile sensing. Herein, we used a genetic algorithm (GA) and a discrete particle swarm optimization algorithm (DPSO) to manage the complexity of the problem, compute feasible and quasi-optimal trajectories for mobile sensors, and determine the demand for movement among nodes. Simulations revealed that the GA produced trajectories significantly superior to those produced by the DPSO in terms of total traveled distance and balance of residual energy.

For a sensing network comprising multiple directional sensors, maximizing the number of covered targets but minimizing sensor energy use is a challenging problem. Directional sensors that can rotate to modify their sensing directions can be used to increase coverage and decrease the number of activated sensors. Solving this target coverage problem requires creating an optimized schedule where (1) the number of covered targets is maximized and (2) the number of activated directional sensors is minimized. Herein, we used a discrete particle swarm optimization algorithm (DPSO) combined with genetic operators of the genetic algorithm (GA) to compute feasible and quasioptimal schedules for directional sensors and to determine the sensing orientations among the directional sensors. We simulated the hybrid DPSO with GA operators and compared its performance to a conventional greedy algorithm and two evolutionary algorithms, GA and DPSO. Our findings show that the hybrid scheme outperforms the greedy, GA, and DPSO algorithms up to 45%, 5%, and 9%, respectively, in terms of maximization of covered targets and minimization of active sensors under different perspectives. Finally, the simulation results revealed that the hybrid DPSO with GA produced schedules and orientations consistently superior to those produced when only DPSO was used, those produced when only GA was used, and those produced when the conventional greedy algorithm was used.

A mobile ad hoc network (MANET) is a system of wireless mobile nodes dynamically self-organizing in arbitrary and temporary network topologies. Frequent topology changes caused by node mobility make the raising of the packet delivery fraction in MANET a challenging problem. In this paper, we propose a scheme to improve packet delivery fraction of the ad hoc on-demand distance vector (AODV) protocol and compare it with the performance of several routing protocols. A variety of scenarios using a variety of pause time and size of the ad hoc network were simulated.

One of the research areas in radio-frequency identification (RFID) systems is the reduction of the identification processing time for a number of tags within an RFID reader recognition region. In the last decade, many research results regarding anticollision algorithms have been presented in the literature. Most of them are tree-based protocols. However, it is important for tree-based protocols to enhance stability and system throughput, since they may face long identification delays when the network density is high. In this study, we present a highly efficient predetection tree-based algorithm to achieve more efficient tag identification performance. Our proposed mechanism can effectively reduce both collisions and idle cycles by exploiting the predetection technique and adjustable slot size mechanism. The simulation results show that the proposed mechanism can effectively improve tag identification time performance by around 29.9% to 64.8% over previous techniques. Further, the number of query cycles, number of collisions, and total number of slots are reduced compared to previous predetection-based protocols. It is also observed that the proposed scheme can have good performance in large-scale RFID systems.

A mobile ad hoc network (MANET) is characterized by multi-hop wireless links, absence of a fixed infrastructure, and frequent host mobility. Frequent topology change caused by node mobility makes it a challenging problem to raise packet delivery ratio. In this paper, we propose a scheme to improve existing Ad hoc On-Demand Distance Vector (AODV) protocols by creating multiple alternate routes with little overhead, resulting in better performance in packet delivery ratio. The advantage of the broadcast nature of wireless communications is used in this extended AODV protocol named AODV-MM (AODV with meshed multipath) to achieve link-disjoint multipath with better packet delivery ratio and lower overhead. The experimental results show the better performance in high mobility and heavy traffic load environment, compared with several routing protocols.