In order to optimize the environmental factors for cucumber growth, a fertilizer and water control system was designed based on the Internet of Things (IoT) system. The IoT system monitors environmental factors such as temperature, light and soil Ec value, and uses image processing to obtain four growth indicators such as cucumber stem height, stem diameter size, number of leaves and number of fruit set to establish a single growth indicator model for temperature, light, soil Ec value and growth stage, and the four growth indicators were fused to obtain the comprehensive growth indicator I_c for cucumber, and calculates its deviation to determine the cucumber growth status. Based on the integrated growth index I_c of cucumber, a soil Ec control model was established to provide the optimal environment and fertilizer ration for cucumber at different growth stages to achieve stable and high yield of cucumber.

Lettuce (Lactuca sativa L.) is the main leafy vegetable grown in Brazil. Its productivity and quality are limited by the growing season, the nearby environment and the type of cultivar adopted. The objective of this work was to verify at different times of the year the best planting environment for lettuce cultivation in a semi-humid tropical climate. For this purpose, an experiment was set up in three different seasons (October–November 2014, January–March, May–July 2015). The experimental design was randomized blocks, in a 3 × 3 × 2 factorial arrangement, consisting of three seasons, three cultivars (cvs. Vera^®, Tainá^® and Rafaela^®) and two growing environments (low tunnel with beds protected with mulching consisting of soil protection with plastic fabric covering, and beds without protection or conventional cultivation) and four replicates per treatment. Plant biomass, stem length, head diameter, number of leaves per head and crop productivity were evaluated as response parameters. The results showed that the May–July period favored biomass production, head diameter and productivity. Despite the similarity between varieties, the variety Vera^® is more productive in biomass, number of leaves per head, stem length and productivity. The low tunnel planting system with mulching is adequate under the conditions evaluated for lettuce cultivation. This system in the May–July period favors a superior development in the characteristics biomass, head diameter and productivity, if compared to conventional cultivation during the October–November period.

Many questions of control theory are well studied for systems which satisfy to the relative degree definition. If this definition is fulfilled then there exists linear state-space transform reducing system to a very convenient canonical form where zero dynamics is a part of system’s equations. Algorithms of such reduction are well-known. However, there exist systems which don’t satisfy this definition. Such systems are the subject of investigation in the presented paper. To investigate their properties here we suggest to consider an analogue of the classical relative degree definition – the so-called column-wise relative degree. It turned out that this definition is satisfied in some cases when classical relative degree doesn’t exist. We introduce this notion here, investigate it properties and suggest algorithm for reducing systems to the column-wise relative degree compliant form if possible. It is possible to show that systems with column-wise relative degree also can be reduced to a convenient canonical form by a linear state-space transformation. Some problems arise from the fact that some systems which do not have relative degree can be reduced to a form with it using linear inputs or outputs transform. Here we show that this is an interesting mathematical problem, which can be solved with the help of properties of relative degree, formulated and proved in this paper.

The idea of a smart city has evolved in recent years from limiting the city’s physical growth to a comprehensive idea that includes physical, social, information, and knowledge infrastructure. As of right now, many studies indicate the potential advantages of smart cities in the fields of education, transportation, and entertainment to achieve more sustainability, efficiency, optimization, collaboration, and creativity. So, it is necessary to survey some technical knowledge and technology to establish the smart city and digitize its services. Traffic and transportation management, together with other subsystems, is one of the key components of creating a smart city. We specify this research by exploring digital twin (DT) technologies and 3D model information in the context of traffic management as well as the need to acquire them in the modern world. Despite the abundance of research in this field, the majority of them concentrate on the technical aspects of its design in diverse sectors. More details are required on the application of DTs in the creation of intelligent transportation systems. Results from the literature indicate that implementing the Internet of Things (IoT) to the scope of traffic addresses the traffic management issues in densely populated cities and somewhat affects the air pollution reduction caused by transportation systems. Leading countries are moving towards integrated systems and platforms using Building Information Modelling (BIM), IoT, and Spatial Data Infrastructure (SDI) to make cities smarter. There has been limited research on the application of digital twin technology in traffic control. One reason for this could be the complexity of the traffic system, which involves multiple variables and interactions between different components. Developing an accurate digital twin model for traffic control would require a significant amount of data collection and analysis, as well as advanced modeling techniques to account for the dynamic nature of traffic flow. We explore the requirements for the implementation of the digital twin in the traffic control industry and a proper architecture based on 6 main layers is investigated for the deployment of this system. In addition, an emphasis on the particular function of DT in simulating high traffic flow, keeping track of accidents, and choosing the optimal path for vehicles has been reviewed. Furthermore, incorporating user-generated content and volunteered geographic information (VGI), considering the idea of the human as a sensor, together with IoT can be a future direction to provide a more accurate and up-to-date representation of the physical environment, especially for traffic control, according to the literature review. The results show there are some limitations in digital twins for traffic control. The current digital twins are only a 3D representation of the real world. The difficulty of synchronizing real and virtual world information is another challenge. Eventually, in order to employ this technology as effectively as feasible in urban management, the researchers must address these drawbacks.

The challenge of rural electrification has become more challenging today than ever before. Grid-connected and off-grid microgrid systems are playing a very important role in this problem. Examining each component’s ideal size, facility system reactions, and other microgrid analyses, this paper proposes the design and implementation of an off-grid hybrid microgrid in Chittagong and Faridpur with various load dispatch strategies. The hybrid microgrids with a load of 23.31 kW and the following five dispatch algorithms have been optimized: (i) load following, (ii) HOMER predictive, (iii) combined dispatch, (iv) generator order, and (v) cycle charging dispatch approach. The proposed microgrids have been optimized to reduce the net present cost, CO₂ emissions, and levelized cost of energy. All five dispatch strategies for the two microgrids have been analyzed in HOMER Pro. Power system reactions and feasibility analyses of microgrids have been performed using ETAP simulation software. For both the considered locations, the results propound that load-following is the outperforming approach, which has the lowest energy cost of $0.1728/kWh, operational cost of $2944.13, present cost of $127,528.10, and CO₂ emission of 2746 kg/year for the Chittagong microgrid and the lowest energy cost of $0.2030/kWh, operating cost of $3530.34, present cost of 149,287.30, and CO₂ emission of 3256 kg/year for the Faridpur microgrid with a steady reaction of the power system.