Autonomous Mobile Robotic System for Environment Monitoring in a Coastal Zone

Kurkin, Andrey; Tyugin, Dmitry; Kuzin, V.D.; Чернов, А. А.; Makarov, Vladimir; Beresnev, P. O.; Filatov, V. I.; Зезюлин, Д. В.

doi:10.1016/j.procs.2017.01.022

Cited by 17 publications

(4 citation statements)

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“…Some also rely on laptop or PC to monitor [3]. For example, the work in [4] is designed coastal monitoring [5] designed a mobile robot for mowing, both of which due to its size and application, are well above USD 500. While both of these systems are properly equipped with the appropriate sensors, these rovers can't be used to monitor tight and confined spaces such as the air vent and the design is too big.…”

Section: Literature Reviewmentioning

confidence: 99%

Low-cost environmental monitoring mini rover based on IoT technology

Pauzi¹,

Mustaza²,

Yahya³

2021

IJATEE

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The aim of this research is to construct a rover for environmental condition monitoring, as an alternative for conventional monitoring system and data gathering via the use of closed-circuit TV (CCTV), personnel and detection animal. The system can be deployed to assess damage and toxicity of areas based on reading from sensors, and for monitoring through visual image from the camera. The rover employs the Internet-of-Things (IoT) concept and is able to monitor the condition of the environment via the help of sensors such as humidity sensor, temperature sensor, air quality sensor, ultrasonic sensor and also with the help of camera. The developed rover will be controlled by a mobile application as the GUI, and the data from the sensor and the camera image can be monitored through the mobile application. If obstacle is detected by the ultrasonic sensor, the mobile application will give notification towards the user through the mobile application, to warn of possible collision. The data from the sensor is sent to the MySQL database and the system is connected via Wi-Fi. The data can be accessed by the user later and can also be used to perform further analysis ifneeded. This rover is compact in size, able to enter areas that are hard to access, and its usage will lower the cost of monitoring with lower development cost of the rover.

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Section: Literature Reviewmentioning

confidence: 99%

Low-cost environmental monitoring mini rover based on IoT technology

Pauzi¹,

Mustaza²,

Yahya³

2021

IJATEE

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show abstract

“…In sensor networks, the problem of estimating the state observed by multiple sensors has been analyzed extensively in recent decades due to the variety of applications they have in signal processing (see, e.g., [1][2][3][4][5][6][7][8][9]).…”

Section: Introductionmentioning

confidence: 99%

An Optimal Linear Fusion Estimation Algorithm of Reduced Dimension for T-Proper Systems with Multiple Packet Dropouts

Fernández-Alcalá

Jiménez‐López

Bihan

et al. 2023

Sensors

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This paper analyses the centralized fusion linear estimation problem in multi-sensor systems with multiple packet dropouts and correlated noises. Packet dropouts are modeled by independent Bernoulli distributed random variables. This problem is addressed in the tessarine domain under conditions of T1 and T2-properness, which entails a reduction in the dimension of the problem and, consequently, computational savings. The methodology proposed enables us to provide an optimal (in the least-mean-squares sense) linear fusion filtering algorithm for estimating the tessarine state with a lower computational cost than the conventional one devised in the real field. Simulation results illustrate the performance and advantages of the solution proposed in different settings.

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“…Multisensor systems and data fusion techniques are receiving increasing research and practical attention due to their ability to provide more robust estimation procedures than those that use a single sensor, as well as their broad applications in fields such as robotics, image processing, autonomous navigation, and smart homes, among others [1][2][3][4][5]. In estimation problems from noisy sensor measurements, the best known and most widely applied procedure is the Kalman filter and its different extensions, which are based on a state-space system (see, for example, [5][6][7][8]).…”

Section: Introductionmentioning

confidence: 99%

Multisensor Fusion Estimation for Systems with Uncertain Measurements, Based on Reduced Dimension Hypercomplex Techniques

et al. 2022

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The prediction and smoothing fusion problems in multisensor systems with mixed uncertainties and correlated noises are addressed in the tessarine domain, under Tk-properness conditions. Bernoulli distributed random tessarine processes are introduced to describe one-step randomly delayed and missing measurements. Centralized and distributed fusion methods are applied in a Tk-proper setting, k=1,2, which considerably reduce the dimension of the processes involved. As a consequence, efficient centralized and distributed fusion prediction and smoothing algorithms are devised with a lower computational cost than that derived from a real formalism. The performance of these algorithms is analyzed by using numerical simulations where different uncertainty situations are considered: updated/delayed and missing measurements.

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Autonomous Mobile Robotic System for Environment Monitoring in a Coastal Zone

Cited by 17 publications

References 1 publication

Low-cost environmental monitoring mini rover based on IoT technology

Low-cost environmental monitoring mini rover based on IoT technology

An Optimal Linear Fusion Estimation Algorithm of Reduced Dimension for T-Proper Systems with Multiple Packet Dropouts

Multisensor Fusion Estimation for Systems with Uncertain Measurements, Based on Reduced Dimension Hypercomplex Techniques

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