Alexandru Dumitrascu

Remote Monitoring and Control System for Environment Applications

This article treats the issue of remote monitoring and control of greenhouse environment through a distributed system that interconnects several subsystems. Thus, a wireless data acquisition subsystem, a fully automated subsystem made of PLCs and industrial communication networks and an irrigation subsystem consists of two water tanks, sensors and actuators are interconnected. According to data provided by sensors, the automatic control subsystem decides whether the irrigation cycle of plants should be performed. In this case, it provides corresponding commands to irrigation subsystem. Moreover, two graphical interfaces (eKo-View and eKo-GreenHouse) are added of the process and presented in detail in this paper.

ASTANK2: Analytical Modeling and Simulation

The paper focuses on building the mathematical model of a filling/drainage process (namely ASTANK2), by analytical approach. Models are subsequently tested by simulation. The process is versatile: it consists of two tanks with different geometric shape, which could be considered in independent or coupled setup and are supplied by an adjustable water distribution pipelines network. The proposed model is nonlinear and can be defined in various configurations, by connecting the desired component models, from the available ones. A simulator that integrates these components is implemented in MATLAB-SIMULINK environment. Its goal is twofold: to simulate the plant dynamics according to several scenarios, on one hand, and to validate the proposed analytical model, on the other hand. Some simulation results are presented in the end.

Reducing Risks in Agriculture

Agricultural risks are discussed because of the disasters related to the water regime disturbance. Different tools are considered in framework of the remote-sensing and in-situ monitoring. Global Information-Modeling System (GIMS) is proposed as effective information technology for monitoring data analysis and processing. The GIMS basis is given. Two versions of optical systems are considered for the water quality diagnostics. Algorithm is proposed to the optical spectral images recognition. Examples of simulation experiments with the GIMS-based tools are given.

A New Challenge in Ecological Process Control Based on PLCs with Profinet Communication Protocol

The current situation of environmental resources requires their efficient usage through efficient process control. But, process control can not be achieved without an essential component: the communication between all devices, such as sensors, controllers, actuators, programming stations etc. The aim is to achieve the irrigation process of plants in greenhouse conditions. Therefore, it is submitted a comprehensive application that proposes to be a distributed control system including data acquisition and processing, both local and remote monitoring of the process parameters. The distributed system is based on modern equipment: Siemens Simatic PLCs and HMI, Memsic e̅Ko Pro wireless sensors network, level sensors for irrigation tanks and actuators such as on/off valves and pumps. In terms of communication between equipments, an industrial bus and protocols were used - Profinet and wireless communication. The software part is provided by TIA Portal with STEP 7 and WinCC flexible RT and LOGO! Soft Comfort for programming the automation devices. ModbusTCP was used to develop the communication protocol between central devices.

An Effective Tool for the Tropical Cyclones Monitoring

It has been recently suggested that concrete processes occurring on the Sun (e.g. sunspots) significantly affect the tropical cyclogenesis. Despite this finding the current understanding of the processes that generate tropical cyclones is still limited. We herewith present a new complex monitoring tool for the collection and storage of relevant environmental information to solve the problem of the tropical cyclone prediction. More specifically, a three-level methodology for making decisions on the dynamical evolution of the ocean-atmosphere system is suggested. This methodology is based on a recently proposed environmental instability indicator and the use of sequential analysis process within which a stage of training is established, when all boundaries are located. Effectiveness of this methodology is assessed by examination of several examples of tropical hurricanes. More specifically, it is demonstrated how this tool can be employed to monitor the tropical hurricanes, like Katrina (2005), Irene (2011) and Isaac (2012).

Environment Communication and Control Systems Integrated on Teaching Platforms: Case Study: Double Water Tank System

This paper introduces a solution for integrating environment systems on teaching platforms using two components: communication and primary control. The communication relies on a bus and specific protocol. The primary control algorithms were implemented in MATLAB-SIMULINK environment, while using Siemens S7-1200 PLC as acquisition server and some regular PC as a client, communicating to each other through the Mudbugs-TCP protocol. The teaching platform is represented by the double water tank system ASTANK2, after being equipped with sensors and actuators.

Geoecological Information-Modeling System as a Tool for Global Environmental Diagnostics

New information–modeling technology is developed, to be as a tool for the diagnostics of climate-nature-society system with the view of sustainable development strategies. The questions of environmental monitoring system synthesis are discussed with the use of different instrumental means. Complex of models and algorithms is listed to be as a base of information-modeling technology. Examples of simulation modeling results are given to demonstrate the possibilities of proposed information-modeling system.

Intelligent Forecasting of Indoors Ecological Processes

The paper addresses the problem of real-time monitoring and intelligent forecasting for indoors ecological phenomena. The process yields a collection of ecological parameters viewed as distributed time series. Data acquired by means of a wireless network of sensors are modeled by using complex algorithms in view of prediction. An evolutionary searching strategy (Particle Swarm Optimization-PSO) is proposed in order to intelligently find the most accurate prediction model. This strategy is adapted to predictors like PARMA, PARMAX, KARMA and FORWAVER, which are implemented within the monitoring and forecasting system, in order to estimate the future evolution of some ecological parameters. The monitoring system was effectively integrated in an industrial application dealing with automatic irrigation of a small greenhouse. The forecasting simulation results with real data and a comparative assessment of best predictor performances obtained with PSO are presented in the end.