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One of the most challenging aspects of waste generation collection occurs during working hours. Sensors in smart cities are used to track the actual conditions of waste generation. These sensors assist in the monitoring of bin usage. However, controlling a single bin is impractical and requires many resources. Another approach will be to use historical data to assist decision-makers. Thus, based on historical data, this paper proposes an appropriate and effective method using recurrent neural networks (RNNs) to predict waste generation levels in smart cities. [ABSTRACT FROM AUTHOR]

As the world population is rising rapidly, there is a fast depletion of resources. So to meet the requirements of increasing population, innovation is required especially in the field of agriculture. In Precision agriculture, smart sensors are used to impart data which helps the farmers in monitoring and optimizing the crop production along with record of changing environmental factors. IoT and sensor networks play a vital role in agriculture. The agricultural industry is being transformed with the use of sensors, software and AI. Combinational sensors and sensor hardware gives the data that helps in increasing the crop production and producing high yield crops which are disease free to keep pace with the increasing demand for food. This article presents a review of precision agriculture, soil less agriculture and sensors used in precision agriculture. [ABSTRACT FROM AUTHOR]

The rapid development of the intelligent systems, which process data received from various types of sensors, raises the question for the change in the nature of the information they provide. In the proposed material is attempted to analyze the nature of the change of the a posteriori information for the presence of a certain type of events, processes, phenomena or objects received by sensors in the process of monitoring and analysis of the environment in which they operate. Because of natural and man-made interferences in the environment, in which operate the intelligent systems and the sensors, the decisions of the sensors are of a random nature. It is accepted, that the decisions of the intelligent systems are based on the criterion of minimum average risk or on derived from its criteria for a maximum ratio between the a posteriori probabilities for the presence or absence of the corresponding object, phenomenon or event. As an absolute maximum of this ratio can be achieved after an infinite number of decision-taking cycles by the sensors, the introduction of a threshold value for this ratio is proposed in this study. In the paper are examined one of the most common types of sensors - those working in discreet mode of operation. A mathematical description of the change of the a posteriori probability for the existence of a certain type of events, processes, phenomena or objects is proposed, and the dependence of this probability on the main characteristics of the sensors is analyzed. [ABSTRACT FROM AUTHOR]

Deflection sensors have attracted significant attention due to their wide application in pressure and temperature measurements in practical systems. Several techniques have been proposed, studied, and tested to realize optical deflection sensor elements, including Mach-Zehnder (MZI), and Fabry-Pérot interferometers. In this work, a novel optical deflection sensor that is comprised of two cascaded optical resonators is proposed and analyzed. The proposed structure is designed to operate in the multi-stable (input to output) regime. As the first resonator is equipped with a movable mirror, which is connected to a diaphragm in order to sense changes in deflection, the second resonator is filled with non-linear material. It is demonstrated that such a structure has a novel memory property, aside from having the ability to yield instant deflection measurements. This novel property is attributed to the non-linear refractive index of the medium of the second resonator. Furthermore, the sensor sensitivity (which is the ratio of the change in the output light intensity to the change in the induced deflection) is enhanced due to the input-output multi-stable behavior of the proposed structure. This device possesses a promising potential for applications in future smart sensors. [ABSTRACT FROM AUTHOR]