Deep learning-based decision support system for weeds detection in wheat fields

<span>In precision farming, identifying weeds is an essential first step in planning an integrated pest management program in cereals. By knowing the species present, we can learn about the types of herbicides to use to control them, especially in non-weeding crops where mechanical methods that are not effective (tillage, hand weeding, and hoeing and mowing). Therefore, using the deep learning based on convolutional neural network (CNN) will help to automatically identify weeds and then an intelligent system comes to achieve a localized spraying of the herbicides avoiding their large-scale use, preserving the environment. In this article we propose a smart system based on object detection models, implemented on a Raspberry, seek to identify the presence of relevant objects (weeds) in an area (wheat crop) in real time and classify those objects for decision support including spot spray with a chosen herbicide in accordance to the weed detected.</span>

Smart system for maintaining aquascape environment using internet of things based light and temperature controller

<span>The purpose of this research is to create a smart system based on internet of things (IoT) application for a plant aquarium. This smart system helps users to maintain the environment's parameters of the plant aquarium. In this study, the parameters to be controlled by the system are light intensity and temperature. The hardware used to develop this system is the ESP32 as the microcontroller, BH1750FVI as the light sensor, high power led (HPL) light-emitting diodes (LED) lamp as the light source, DS18B20 as temperature sensor, the heater, and the 220 VAC fan that is used to raise and lower the temperature. In this study also developed an application that is used by the user to provide input to the system. The developed application is then installed on the user's smartphone and used to connect the user to the system via the internet. The ease of adding and removing devices used on the system is a capability that is also being developed in this smart system. The developed system can produce light intensity with accuracy rate of 96% and always manage to keep the temperature within the predetermined range.</span>

Polyelectrolyte Complexes of Ciprofloxacin and Lidocaine Improve Wound Healing in Deep Second Degree Burns and Reduce in Vitro Ciprofloxacin Cytotoxicity in Fibroblasts

The development of new treatments capable of controlling infections and pain related to burns continues to be a challenge. Antimicrobials are necessary tools, but these can be cytotoxic for regenerating cells.In this study, antibiotic-anesthetic smart systems obtained by ionic complexation of polyelectrolytes with ciprofloxacin and lidocaine were obtained as film and hydrogel. The complexation of ciprofloxacin with natural polyelectrolytes efficiently contributed to increasing biocompatibility in a primary culture of isolated fibroblasts. In addition, the relative levels of the proteins integrin β1 and p-FAK involved in cell migration were increased with no modifications in cell mobility. Their evaluation in a deep second-degree burn model revealed fast reepithelization, with appendage conservation and complete dermis organization. Encouragingly, we found that both the film and the hydrogel showed a significantly superior performance compared to the reference treatment of silver sulfadiazine cream. This work highlights the great potential of this smart system as an attractive dressing for burns, which surpasses currently available treatments.

Artificial Intelligence in Human Resource Practices With Challenges and Future Directions

Artificial intelligence is a branch of science and technology that has been used effectively over the decades in various fields, and now it has become an indispensable part of organizational practices as it is one of the leading technologies in the current era, and now there is an emerging trend of applying AI technologies within the businesses. The central necessity of human resource management is also majorly based on technological approaches as it became a potential need for any human resources department to perform its role in the development of the whole organization. Technologies based on AI are and will be the smart system of the future and it's also changing the processes of human resource management by making it more dependent on advanced technologies. Through the chapter, the researcher will get to know the artificial technologies being practiced in HR practices and explore the probable and potential of technicality of AI in HRM and also the challenges associated with AI in HRM and its future possibilities.

Monitoring, Predicting, and Optimizing Energy Consumptions

Energy consumption and, consequently, the associated costs (e.g., environmental and monetary) concern most individuals, companies, and institutions. Platforms for the monitoring, predicting, and optimizing energy consumption are an important asset that can contribute to the awareness about the ongoing usage levels, but also to an effective reduction of these levels. A solution is to leave the decisions to smart system, supported for instance in machine learning and optimization algorithms. This chapter involves those aspects and the related fields with emphasis in the prediction of energy consumption to optimize its usage policies.

Smart Aero-Spider: An adaptive and selective smart switching aerator system

The recovery from the COVID-19 pandemic hit shows the emergence of increase in quality of life across various parts of the world. With this lifestyle change, people are looking towards high quality food. Fish being a major source of protein, the industry producing fish from aquaculture is booming. The proposed smart aerator system provides an integrated array of underwater systems for selective aeration of the water body. The smart system ensures targeted aeration to guarantee optimal levels of dissolved oxygen at all times. This is beneficial for perfect survival, growth, and reproduction of fishes. The strategically placed spider aerators are turned on when readings from the dissolved oxygen level at the location is below the optimum range of values. The air blower system consists of an intelligent switching system to activate the right aerator based on the requirement. The sensor data is relayed to the cloud with a wireless communication module. This data can be used for useful insights and all-round monitoring of the water body. The respective aerators have IR sensor to detect movement alongside on-board LEDs to indicate functioning status. Overall, this ensures maximum accelerated growth of healthy fishes. Thus, the solution aims at efficiently boosting the ability of the aquaculture industry to meet the ever-growing demand of consumers.