Совершенствование системы противопожарного мониторинга лесов путем расширения информационно-технологических возможностей современных квадрокоптеров

The article proposes a solution to an important problem - the development of an information technology based on expanding the functionality of non-specialized unmanned aerial vehicles (drones) for early detection of forest fires. The proposed information technology is designed to increase the effectiveness of monitoring forest fires. Тhe existing level of information technology does not fully settle the issue of reliable fire protection of forests. Today, there is a contradiction between the high cost of developing high-tech fire-fighting equipment and lack of its efficiency. The elimination of this contradiction will be facilitated by the involvement of additional non-technical and technical resources in the information technology of early detection of forest fire hotspots. The results of the analysis of the use of modern drones prove that the involvement of unmanned aerial vehicles significantly increases the efficiency of many types of monitoring and they can successfully be used to solve the problems of early detection of forest fire hotspots. The results of experiments are presented, which were carried out both for a series of digital images and for video

Prolonging Wireless Sensor Network Lifetime Using Routing Protocol

Prolonging network lifetime is one of the challenging issues of Wireless Sensor Networks (WSN). Many techniques have been proposed to achieve a longer battery life for the sensor nodes. In this paper, we focus on the routing technique to improve the battery life and extend the network lifetime. Our protocol is based upon the two existing protocols, namely, LEACH (Low-Energy Adaptive Clustering Hierarchy) and PEGASIS (Power Efficient GAthering in Sensor Information Systems). By combining these two basic routing techniques, we propose a new protocol which provides an increase in network lifetime compared to the existing basic protocols

Stochastic Approach for Energy-Efficient Clustering in WSN

Abstract- Wireless sensor networks are self-organizing networks in which sensor nodes with limited resource are scattered in an area of interest to gather information. WSNs need to have effective node2019;s energy management methods for stable and seamless communication. Power efficient clustering is done in WSN to prolong the life of the network. In WSN, many algorithms are developed to save energy of sensor nodes and to increase the lifetime of the network. This paper provides an energy efficient clustering algorithm inspired by prophet routing protocol to enhance the cluster based operation of the nodes. Adaptive learning is implemented for head selection for efficientcommunication. Simulation results confirm the efficiency of the mechanism

A survey on robotic technologies for forest firefighting: Applying drone swarms to improve firefighters’ efficiency and safety

Forest firefighting missions encompass multiple tasks related to prevention, surveillance, and extinguishing. This work presents a complete survey of firefighters on the current problems in their work and the potential technological solutions. Additionally, it reviews the efforts performed by the academy and industry to apply different types of robots in the context of firefighting missions. Finally, all this information is used to propose a concept of operation for the comprehensive application of drone swarms in firefighting. The proposed system is a fleet of quadcopters that individually are only able to visit waypoints and use payloads, but collectively can perform tasks of surveillance, mapping, monitoring, etc. Three operator roles are defined, each one with different access to information and functions in the mission: Mission commander, team leaders, and team members. These operators take advantage of virtual and augmented reality interfaces to intuitively get the information of the scenario and, in the case of the mission commander, control the drone swarmThis research received no external fundin

ESTUDO COMPARATIVO DE TECNOLOGIAS PARA DETECÇÃO PRECOCE DE INCÊNDIOS FLORESTAIS EM ÁREAS DE REFLORESTAMENTO NO BRASIL

É clara a constatação que a problemática dos incêndios florestais atinge todas as áreas do planeta. Também é evidente que o assunto não é novo e portanto, muitos esforços para o desenvolvimento de tecnologias e métodos que possam mitigar esta situação vêm sendo feitos há muitos anos. O objetivo desta pesquisa é iluminar o tema trazendo uma visão ampliada sobre o cenário das tecnologias em uso e/ou em estudo acerca da detecção precoce de incêndios florestais nos últimos anos.Como síntese, podemos destacar que as tecnologias baseadas em vídeo, representam o maior número de menções e de artigos publicados.Também podemos afirmar que não há a solução isenta de pontos fracos nem ideal para todas as situações.Como produto deste projeto, buscou-se fornecer elementos para que o tomador de decisão tenha informações consistentes no momento de decidir qual modelo de Sistema melhor atende suas necessidades na busca por Sistemas automatizados para a Detecção Precoce de Incêndios Florestais

Design and Field Test of a WSN Platform Prototype for Long-Term Environmental Monitoring

Long-term wildfire monitoring using distributed in situ temperature sensors is an accurate, yet demanding environmental monitoring application, which requires long-life, low-maintenance, low-cost sensors and a simple, fast, error-proof deployment procedure. We present in this paper the most important design considerations and optimizations of all elements of a low-cost WSN platform prototype for long-term, low-maintenance pervasive wildfire monitoring, its preparation for a nearly three-month field test, the analysis of the causes of failure during the test and the lessons learned for platform improvement. The main components of the total cost of the platform (nodes, deployment and maintenance) are carefully analyzed and optimized for this application. The gateways are designed to operate with resources that are generally used for sensor nodes, while the requirements and cost of the sensor nodes are significantly lower. We define and test in simulation and in the field experiment a simple, but effective communication protocol for this application. It helps to lower the cost of the nodes and field deployment procedure, while extending the theoretical lifetime of the sensor nodes to over 16 years on a single 1 Ah lithium battery

The Acceptance of Using Information Technology for Disaster Risk Management: A Systematic Review

The numbers of natural disaster events are continuously affecting human and the world economics. For coping with disaster, several sectors try to develop the frameworks, systems, technologies and so on. However, there are little researches focusing on the usage behavior of Information Technology (IT) for disaster risk management (DRM). Therefore, this study investigates the affecting factors on the intention to use IT for mitigating disaster’s impacts. This study conducted a systematic review with the academic researches during 2011-2018. Two important factors from the Technology Acceptance Model (TAM) and others are used in describing individual behavior. In order to investigate the potential factors, the technology platforms are divided into nine types. According to the findings, computer software such as GIS applications are frequently used for simulation and spatial data analysis. Social media is preferred among the first choices during disaster events in order to communicate about situations and damages. Finally, we found five major potential factors which are Perceived Usefulness (PU), Perceived Ease of Use (PEOU), information accessibility, social influence, and disaster knowledge. Among them, the most essential one of using IT for disaster management is PU, while PEOU and information accessibility are more important in the web platforms

Practical Evaluation of Low-complexity Medium Access Control Protocols for Wireless Sensor Networks

This thesis studies the potential of a novel approach to ensure more efficient and intelligent assignment of capacity through medium access control (MAC) in practical wireless sensor networks (WSNs), whereby Reinforcement Learning (RL) is employed as an intelligent transmission strategy. RL is applied to framed slotted-ALOHA to provide perfect scheduling. The system converges to a steady state of a unique transmission slot assigned per node in single-hop and multi-hop communication if there is sufficient number of slots available in the network, thereby achieving the optimum performance. The stability of the system against possible changes in the environment and changing channel conditions is studied. A Markov model is provided to represent the learning behaviour, which is also used to predict how the system loses its operation after convergence. Novel schemes are proposed to protect the lifetime of the system when the environment and channel conditions are insufficient to maintain the operation of the system. Taking real sensor platform architectures into consideration, the practicality of MAC protocols for WSNs must be considered based on hardware limitations/constraints. Therefore, the performance of the schemes developed is demonstrated through extensive simulations and evaluations in various test-beds. Practical evaluations show that RL-based schemes provide a high level of flexibility for hardware implementation