Many researchers employ IEEE802.15.4 as communication technology for wireless sensor networks (WSNs). However, medium access control (MAC) layer requirements for communications in wireless sensor networks (WSNs) vary because the network is usually optimized for specific applications. Thus, one particular standard will hardly be suitable for every possible application. Two general categories of MAC techniques exist: contention based and schedule based. This paper explains these two main approaches and includes examples of each one. The paper concludes with a unique performance analysis and comparison of benefits and limitations of each protocol with respect to WSNs.
One of the biggest problems with distribution systems correspond to the load unbalance created by power demand of customers. This becomes a difficult task to solve with conventional methods. Therefore, this paper uses integer linear programming and Branch and Bound algorithm to balance the loads in the three phases of the distribution system, employing stored data of power demand. Results show that the method helps to decrease the unbalance factor in more than 10%, by selecting the phase where a load should be connected. The solution may be used as a planning tool in distribution systems applied to installations with systems for measuring power consumption in different time intervals. Furthermore, in conjunction with communications and processing technologies, the solution could be useful to implement with a smart grid.
Utility companies in developing countries employ analog electrical meters to determine consumption and bill their customers accordingly. Obtaining an accurate reading is an expensive and time-consuming process. High consumption levels of water, energy, or gas are fined by the government; thus, it is necessary to develop tools that allow users to be informed about their consumption in real time. This paper proposes a new number recognition algorithm named the Hausdorff distance for meter reading (HD MR). Experiments prove that HD MR can achieve a 99.9% recognition rate, even when recognized numbers are under rotation. The maximum recognition time is 31 ms; hence, the proposed method proves to be effective and capable in real time for the task proposed.
Occupational hygiene requires evaluation of different risk sources in the workplace. The level of physical workload may create stress, fatigue and injuries. Therefore, activity monitoring provides valuable information for companies in assessing and solving possible hazards in the workplace. The article presents a system using wearable technology to monitor and evaluate physical workload with in situ measurements. The system uses a smartwatch and a mobile application for Android phones. During workload monitoring, the application displays physiologic variables such as heart rate, calories, body temperature, galvanic skin response and number of steps. Additionally, the system computes absolute and relative cardiac cost, and Frimat coefficients. Tests were performed on 10 individuals from a janitor staff (5 men and 5 women), monitoring every task during their most demanding hour. Results agree with the type of activity developed in different intervals, showing light and very light workload for different tasks in all workers.
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