Monitoring Of Environmental Conditions Research Articles

Sustainable Livestock Management: Strategies for Enhancing Productivity While Reducing Environmental Impact

Sustainable livestock management is increasingly recognized as a critical component in addressing the dual challenges of enhancing agricultural productivity and mitigating environmental impacts. This study employs a qualitative approach through comprehensive literature review and library research to explore effective strategies for sustainable livestock management. The findings reveal that integrating innovative practices such as rotational grazing, agroforestry, and precision feeding can significantly improve livestock productivity while minimizing ecological footprints. Additionally, the adoption of technology, including data analytics and remote sensing, plays a pivotal role in optimizing resource use and monitoring environmental conditions. The research highlights the importance of stakeholder engagement, including farmers, policymakers, and researchers, in fostering a collaborative approach to sustainable practices. Furthermore, the study underscores the necessity of education and training programs to equip livestock producers with the knowledge and skills required for implementing sustainable strategies. By synthesizing existing literature, this article provides a framework for understanding the multifaceted nature of sustainable livestock management and its potential to contribute to food security and environmental sustainability. The insights gained from this research can inform future policies and practices aimed at promoting sustainable livestock systems globally.

Unusual modes of cell and nuclear divisions characterise Drosophila development.

The growth and development of metazoan organisms is dependent upon a co-ordinated programme of cellular proliferation and differentiation, from the initial formation of the zygote through to maintenance of mature organs in adult organisms. Early studies of proliferation of ex vivo cultures and unicellular eukaryotes described a cyclic nature of cell division characterised by periods of DNA synthesis (S-phase) and segregation of newly synthesized chromosomes (M-phase) interspersed by seeming inactivity, the gap phases, G1 and G2. We now know that G1 and G2 play critical roles in regulating the cell cycle, including monitoring of favourable environmental conditions to facilitate cell division, and ensuring genomic integrity prior to DNA replication and nuclear division. M-phase is usually followed by the physical separation of nascent daughters, termed cytokinesis. These phases where G1 leads to S phase, followed by G2 prior to M phase and the subsequent cytokinesis to produce two daughters, both identical in genomic composition and cellular morphology are what might be termed an archetypal cell division. Studies of development of many different organs in different species have demonstrated that this stereotypical cell cycle is often subverted to produce specific developmental outcomes, and examples from over 100 years of analysis of the development of Drosophila melanogaster have uncovered many different modes of cell division within this one species.

Geoecological assessment of oil-contaminated landscapes of the Republic of Bashkortostan

This article focuses on the geoecological assessment of territories affected by oil spills in the Republic of Bashkortostan from 2017 to 2023. The authors identify the main causes and negative consequences of such incidents, including technical failures, non-compliance with safety regulations, and human factors. The study includes an analysis of statistical data characterizing the number and types of spills by year and administrative regions, which highlights the most vulnerable areas, such as Tuymazinsky and Ufimsky districts, as well as the cities of Ufa and Oktyabrsky. Special attention is given to the impact of spills on soil and landscape cover. The authors note significant changes in the morphological, physicochemical, and microbiological properties of soils, leading to ecosystem degradation. An analysis of soil types and landscapes shows that oil spills most frequently occur on leached and dark gray soils, as well as on elevated and undulating plains. The article emphasizes the importance of comprehensive geoecological assessments for planning the region's sustainable development and developing effective measures to prevent such incidents in the future. The authors provide recommendations for improving safety and monitoring measures, as well as the need to implement modern technologies for cleaning contaminated areas. In conclusion, the study underscores the necessity of continuous monitoring and assessment of environmental conditions to minimize the risk of ecological disasters and ensure public safety.

Experimental Design: Implementation of IoT-based drip irrigation to enhance the productivity of Cilembu sweet potato (Ipomoea batatas) cultivation

Effective irrigation methods are crucial for meeting plant water needs while preventing excessive evaporation, soil dryness, and water shortages. Conventional irrigation methods often result in inefficient water distribution, leading to a reduced agricultural productivity. This study aimed to enhance water use efficiency and improve crop yield by employing Internet of Things (IoT)-based drip irrigation systems. The system regulates water supply and monitor environmental conditions using low-power sensor nodes that measure soil moisture, air temperature, humidity, and light intensity. Field experiments were conducted to ascertain optimal water requirements by adjusting irrigation durations to 15, 30, 60, and 120 minutes and modifying water application based on soil moisture levels below 70%. Irrigation scheduling was performed at 6 am and 6 pm. The implementation of IoT-based drip irrigation in Cilembu sweet potato field resulted in a production yield of 44 tons/ha, marking a 45% productivity compared to conventional irrigation methods. Furthermore, water savings of 65% were achieved through the application of IoT-controlled drip irrigation. These results demonstrate the potential of IoT-based systems in optimizing water use and enhancing agricultural productivity, making it a valuable approach for sustainable farming practices.

PERS: Personalized environment recommendation system based on vital signs

The integration of the Internet of Things (IoT) in healthcare has facilitated real-time monitoring of vital signs and environmental conditions. However, existing systems often lack personalized recommendations that consider the interplay between these factors. This work introduces the Personalized Environment Recommendation System (PERS), which leverages a portable device to continuously collect data on key health metrics, including pulse rate and body temperature, alongside environmental parameters. Utilizing Artificial Neural Networks, PERS analyzes the data to generate tailored health recommendations for users. Experimental results demonstrate an accuracy of 98.7%, highlighting the system’s effectiveness in enhancing patient care and supporting informed health decisions. The findings suggest that PERS can significantly improve health monitoring by providing actionable insights based on individual health profiles and environmental contexts.

Monitoring Perishable Commodities Using Cellular IoT: An Intelligent Real-Time Conditions Tracker Design

Perishable product losses can occur throughout postharvest handling. Proper monitoring of key environmental conditions during this period is essential for predicting quality losses throughout their shelf life. This paper presents the design and testing of a portable and compact datalogger for the real-time monitoring of environmental conditions throughout the food supply chain. The device developed incorporates high-precision sensors to measure temperature, relative humidity, CO2 concentration, luminosity and vibrations, as well as wireless communication capabilities for data transmission, simplifying real-time monitoring over existing multi-component systems while keeping costs affordable. Strategies to optimize power consumption allow a month of battery life, being able to cover entire periods of transport and storage, according to the results of the autonomy test performed on the device. The datalogger uses NB-IoT and relies on other wireless communication protocols if not available to send sensor data to a cloud platform. Comparative testing with commercial dataloggers has been carried out to verify correct device measurements, and field testing has validated successful real-time data transmission along an entire refrigerated transport route. The functionality and autonomy of the proposed device meet the needs of live remote monitoring to help reduce food losses.

IoT-based home control system using NodeMCU and Firebase

Integrating Internet of Things (IoT) technology in home control systems has led to a significant advancement in the control and monitoring of home appliances and environmental conditions. This study presents the development of an IoT-based home control system that uses the NodeMCU ESP8266 microcontroller to manage several home appliances. This system connects to a Firebase real-time database to store or retrieve data in real-time. The user interacts with the IoT system through a mobile application named My Home, developed using Java programming language, and this mobile application is also interfaced with the Firebase cloud server. The developed IoT system allows users to control home appliances such as lights, sockets, fans, and cookers, and it also provides real-time updates of environmental parameters, such as temperature and humidity, which are measured by a DHT11 sensor. In addition, a PIR motion sensor was integrated into the system to enhance the home's security by detecting intrusion. The system's hardware functionality is based on a written Arduino code, which establishes Wi-Fi connectivity to a predefined network, communicates with the Firebase database, handles appliance control and manages sensor data. This IoT-based home control system shows the potential of integrating microcontrollers with cloud services to create a smart, responsive and user-friendly home control platform. The developed IoT system offers a foundation for advancements, thereby making it a valuable contribution to the growing field of smart home technology.

Integrated Multimedia Wireless Sensor Node for Comprehensive Lifelogging and Beyond: Design, Development and Applications

This paper introduces the Integrated Multimedia Wireless Sensor Node (IMWSN), a significant advancement in environmental monitoring and lifelogging within Multimedia Wireless Sensor Networks (MWSN). MWSNs, equipped with wearable sensors, are crucial for documenting personal life experiences. However, current MWSNs often lack the ability to fully integrate data across various sensor types, including environmental, visual, and medical sensors. The IMWSN addresses this gap by providing a comprehensive view of an individual's interactions and environment. The IMWSN is composed of multiple modules: a processor module that manages the overall system efficiently, a visual module designed to capture video footage of the surroundings, an environmental module that allows for real-time monitoring of environmental conditions, and a medical module dedicated to recording health-related data of individuals, a process often known as lifelogging. These components are encased in a custom-designed 3D-printed enclosure and powered by a durable 4500mAh mobile battery. System programming and monitoring are facilitated through the user-friendly Arduino IDE, making the experience accessible and customizable. Beyond its primary function in lifelogging, the IMWSN is remarkably versatile and suited for a range of applications. It can function as an action camera, assist in forest fire monitoring, support ambient assisted living environments, and monitor patients' health and daily activities rigorously. This adaptability makes the IMWSN a valuable and essential tool in fields that require extensive data collection and sophisticated analytical capabilities, highlighting its broad potential impact.

Film forming properties of 3D printed polysaccharide based gels and development of CO2 monitoring labels

Polyvinyl alcohol (PVA) has good compatibility with polysaccharides and is suitable for 3D printing inks for preparing food packaging films or smart labels. In this work, the influences of different concentrations of PVA on the 3D printability and film-forming performance of six polysaccharide-based inks were investigated. PVA formed a strong cross-linked network with sodium alginate (SA) and carboxymethyl cellulose (CMC), which enhanced the 3D printability of the gel, and the addition of 7 % PVA increased the printing accuracy of SA by 20.83 times. PVA also facilitated the smooth extrusion of potato starch (PS), pectin (PE), konjac glucomannan (KGM), and xanthan gum (XG) inks in the printing operation and improved their flowability. The surface of 3D printed PVA- polysaccharide film had tiny print texture, no obvious roughness or graininess, smooth surface, soft texture and good shape. However, cracks and wrinkles were found on the surface of the PVA-PS membrane, which were likely related to inappropriate ratios and uneven shrinkage. FTIR and XRD analysis showed that PVA had excellent compatibility with polysaccharides and was fully distributed within the film. A 3 % PVA addition was found to be optimal, as the polysaccharide films exhibited appropriate hydrophilicity, mechanical strength, and flexibility. The color of polysaccharide-based labels containing bromothymol blue (BTB) and methyl red (MR) prepared with 3 % PVA content changed with the change of CO2 concentration. 3D printed labels were successfully used to monitor the changes of CO2 concentration in tomato packaging during storage. This research extends the applicability of 3D-printed smart labels for real-time monitoring environmental conditions of fruits and vegetables storage, particularly CO2 concentration.

Optimizing Agricultural Production Through the Internet of Things: Innovative Solutions to Reduce Food Loss and Waste

Significant food loss and waste along agricultural supply chains is a global challenge that threatens food security and environmental sustainability. This research aims to explore the potential of Internet of Things (IoT) technology as an innovative solution to overcome these problems. Through an interdisciplinary approach that combines agriculture, information technology and sustainability, this research develops an integrated Internet of Things (IoT) system that can efficiently monitor, analyze and manage the entire agricultural supply chain process. The proposed Internet of Things (IoT) solution includes a wireless sensor network for real-time monitoring of environmental conditions, crop growth, and activity on farmland, as well as a cloud-based analytics platform to process data and provide optimal recommendations. In addition, this system also allows food product traceability and information transparency along the supply chain. Respondents who are agricultural managers have a positive perception of the use of Internet of Things (IoT) technology in their agricultural activities. The research instrument (questionnaire) used was also proven to be valid and reliable in measuring related variables. Thus, this research concludes that the application of Internet of Things (IoT) technology in smart farming has great potential to optimize input use, increase crop productivity, and significantly reduce food loss and waste through better monitoring and control along the agricultural supply chain.

Smart Nanocoating‐ an Innovative Solution to Create Intelligent Functionality on Surface

AbstractThe interaction of substrate surfaces with the environment (moisture, heat, pressure, chemicals) has cascade effects on their efficiency, performance, durability due to their susceptibility towards microbial adhesion, spontaneous leaching, impairment, corrosion etc. Many scientific, technological innovations such as smart coating have been discovered for the protection of these surfaces. It is a high‐tech, high value coating capable of responding to environmental impulses. Incorporation of nanofillers, nanomatrices in smart coating improve surface performance by extending service life, provide high durability, high physical coverage, adhesive strength etc. Real‐time monitoring of environmental conditions, structural health could be made possible by sensing coatings. This review predominantly highlights the essential features, design, advancements, applications of smart nanocoatings over elementary nanocoatings. To cover the whole study, drawbacks of traditional coating methods are also discussed. Finally, the research gaps, future perspectives of smart nanocoatings will be overlooked.

Plastic debris exposure and effects in rivers: Boundaries for efficient ecological risk assessment.

Until recently, plastic pollution research was focused on the marine environments, and attention was given to terrestrial and freshwater environments latter. This discussion paper aims to put forward crucial questions on issues that limit our ability to conduct reliable plastic ecological risk assessments in rivers. Previous studies highlighted the widespread presence of plastics in rivers, but the sources and levels of exposure remained matters of debate. Field measurements have been carried out on the concentration and composition of plastics in rivers, but greater homogeneity in the choice of plastic sizes, particularly for microplastics by following the recent ISO international standard nomenclature, is needed for better comparison between studies. The development of additional relevant sampling strategies that are suited to the specific characteristics of riverine environments is also needed. Similarly, we encourage the systematic real-time monitoring of environmental conditions (e.g., topology of the sampling section of the river, hydrology, volumetric flux and velocity, suspended matters concentration) to better understand the origin of variability in plastic concentrations in rivers. Furthermore, ingestion of microplastics by freshwater organisms has been demonstrated under laboratory conditions, but the long-term effects of continuous microplastic exposure in organisms are less well understood. This discussion paper encourages an integrative view of the issues involved in assessing plastic exposure and its effects on biota, in order to improve our ability to carry out relevant ecological risk assessments in river environments.

Advancing food safety standards through technology integration and policy development

Food safety is a critical global concern, directly impacting public health, economic stability, and international trade. With the complexity of modern food supply chains and the rising incidence of foodborne illnesses, traditional food safety measures are often insufficient to address the growing risks. This review explores how integrating advanced technologies and developing robust policies can significantly enhance food safety standards. Technological innovations, including the Internet of Things (IoT), blockchain, artificial intelligence (AI), and automation, offer promising solutions for real-time monitoring, traceability, and predictive analytics in food production and distribution. IoT and sensors enable constant monitoring of environmental conditions like temperature and humidity, while blockchain ensures transparency and traceability across supply chains. AI and machine learning are transforming food safety by predicting contamination risks and optimizing inspection processes, while robotics and automation reduce human error in food processing plants. Alongside technological advancements, policy development plays a crucial role in reinforcing food safety standards. Global harmonization of food safety regulations, stronger enforcement mechanisms, and public-private partnerships are essential for ensuring widespread compliance. Incorporating technology into regulatory frameworks is key to addressing new challenges and maintaining food safety across borders. Governments must also prioritize consumer education and awareness through policies that leverage technology platforms to promote food safety knowledge. Case studies demonstrate the successful application of these technologies in sectors like dairy and meat processing, showcasing the potential for broader industry adoption. However, challenges such as high implementation costs, regulatory lag, and data security concerns remain. This review argues that a synergistic approach combining technological integration with forward-thinking policy development is essential for advancing global food safety standards and safeguarding public health in the future.

A smart monitoring and observation framework for aquaponics ecosystem

Aquaponics is a sustainable and efficient agricultural system that integrates aquaculture with agriculture. This system integrates Internet of Things (IoT) technology in aquaponics systems with the potential to change sustainable agriculture by combining farming of fish (aquaculture) and soilless cultivation of plants (hydroponics) into a single, efficient ecosystem. This paper explores the design and development of a smart aquaponics system that allows aquaponic farming at commercial scale feasible, leveraging IoT to continuously gather data through various sensors, monitor environmental conditions, and automate control processes. The proposed system architecture is based on a three-tier model, ensuring scalability and maintainability. The proposed system consists of a three-layer architecture: the Perception Layer for measuring different environmental factors and controlling them, the Network Layer for data transmission, and the Application Layer for data storage, manipulation, and user interaction. The key components include sensors for monitoring pH, humidity, temperature, sunlight, oxygen levels, and water proximity; devices such as lights, water pumps, fans, and oxygen pumps for environmental control; and an ESP8266 microcontroller for system management. The system's software is developed using C# DOT NET CORE 8.0, React, MySQL, C, and Arduino. The system allows users the ability to maintain optimal conditions for fish and plant growth, notify users of irregularities, and allow remote control through a web application, proving it to be an intelligent, flexible, low-cost, and stable solution for large-scale aquaponics.

The Wind Power Watch, "Guarding" for Safety - Data-Driven Intelligent Deterrence System for Monitoring Ships in Offshore Wind Farms

This study successfully developed a ship monitoring and repulsion system for offshore wind farms aimed at ensuring the safety and stable operation of the wind farms. The system is capable of real-time monitoring of ship activities and environmental conditions, quickly identifying and eliminating potential safety risks. The research content includes various aspects such as ship detection, path tracking, repulsion decision-making, and data processing. The system integrates multi-sensor data, Geographic Information Systems (GIS), Automatic Identification Systems (AIS) for ships, artificial intelligence algorithms, and advanced communication technologies, constructing an efficient and intelligent monitoring and repulsion framework. Field test results indicate that the system exhibits stable performance and efficient monitoring capabilities under harsh weather conditions, while the intelligent voice repulsion function has shown significant effects.

An ultraviolet light data logger for studies of organismal ecology and physiology

Abstract Monitoring environmental conditions over time is essential for understanding how species regulate those conditions to satisfy their physiological needs. Variation in ultraviolet (UV) light exposure, for instance, is crucial for numerous taxa, influencing behaviour as well as essential physiological processes like vitamin D3 synthesis. Yet, despite these considerations, no commercially available data loggers exist to record UV exposures over time, preventing inquiry into this important but neglected fitness demand. To overcome this challenge, I designed the first UV data logger, custom built on the open‐source Arduino platform. This device logs UV exposures (in voltage or converted to UV index) and date‐time information for each UV reading, at user‐defined intervals. The integration of a low‐power timer into the assembly, and its weather‐resistant housing, enables long‐term use (at least several months). The cost of one device (including housing) is under £45/$55 USD. Calibration and performance tests reveal that this device is reliable under various weather conditions and produces accurate UV readings under both artificial lighting and sunlight. Both the device and its customised housing can be easily replicated and expanded upon (e.g. inclusion of additional sensors). Overall, this device represents a crucial first step in our ability to better characterise UV exposure patterns in habitats for physiological ecology studies. Exposure to UV light is adaptive for many types of organisms, both in the wild and in captivity (e.g. zoos and private hobbyists), and so I expect a broad array of scientific and public users alike to benefit from using this device.

Optimalisasi Waktu Produksi Jamur Tiram Melalui Implementasi Sistem Penyiraman Berbasis IoT di UD Zaida Jamur Tiram

The optimization of oyster mushroom production time through the implementation of an Internet of Things (IoT)-based irrigation system at UD Zaida Jamur Tiram aims to enhance efficiency and production quality. This program integrates IoT technology to automate the irrigation process, allowing real-time control and monitoring of environmental conditions. Methods include the design and installation of an automatic irrigation system, technical training for operators, and performance evaluation through production data analysis. Results show a significant increase in time efficiency and consistency in oyster mushroom quality. The implementation of this IoT system is expected to support the sustainability and competitiveness of the oyster mushroom industry at UD Zaida.

IoT - Toxic Gas Detection System in Sewage

The application of IoT and machine learning in gas detection systems for sewage offers an innovative approach to real-time gas detection and enhances environmental safety in industrial and urban environments. This system uses advanced technologies such as the Internet of Things (IoT), machine learning algorithms, and high-performance sensors like the MQ135 and the DHT11 to achieve the best results in the gas concentration measurement and collection. It identifies abnormalities and determines which emission control measures are most effective for specific release points and similar situations. The design of the device includes sensor nodes that are primarily responsible for data collection and a central microcontroller (MCU) that operates a machine learning algorithm for efficient anomaly detection and predictive maintenance. The system uses the IoT connection to regularly send data to cloud platform (Blynk), enabling real time monitoring of gas levels and environmental conditions. The system generates a visual image of the captured data that can be accessed online. Distinctive attributes like accurate gas detection, continuous monitoring, predictive maintenance, remote assessment, and comprehensive data visualization, all contribute to smart decision-making for environmental safety.

Impact of Smart Greenhouse Using IoT for Enhanced Quality of Plant Growth

Greenhouses play a crucial role in manipulating environmental conditions for optimal plant growth. While existing greenhouses enhance control over environmental factors, manual controls such as watering and humidity regulation often lead to suboptimal production and increased costs. This study proposes the development of a smart greenhouse with an automatic control system using fuzzy logic, specifically fuzzy Sugeno, to regulate watering and lighting based on soil moisture, temperature, and light intensity. The system's architecture involves sensor inputs, microcontroller processing, and the activation of actuators, such as UV lights and water pumps. Fuzzy logic is applied to interpret soil moisture and temperature inputs and determine optimal irrigation durations. The system's functionality is tested and validated through functional testing, Blynk application testing, and fuzzy Sugeno testing. Results indicate the successful implementation of the proposed smart greenhouse system. Functional testing demonstrates accurate sensor readings, including temperature and soil moisture. The Blynk application enables real-time monitoring and control of environmental conditions. Fuzzy Sugeno testing validates the irrigation control system, with an average error rate of 1.3%, affirming the system's alignment with desired specifications. Plant testing in different conditions showcases the effectiveness of the smart greenhouse in supporting plant growth and development.

The Automating Aquaponics System With RTC, Turbidity Sensor and Water Level Sensor

Aquaponic system automation is key to increasing agricultural efficiency and productivity. A system that is considered an innovative method of sustainable food production that combines fish farming and agriculture simultaneously. The aim of this research is to implement an IoT system in aquaponics that is connected to various sensors, such as turbidity sensors, water level sensors, and RTC modules. To monitor water quality conditions in tilapia habitats and measure accurate timing to provide fish food automatically to improve fish health and growth and support better and consistent results. This optimized system provides better monitoring of environmental conditions, reduces reliance on manual maintenance, and increases overall productivity. Helps increase tilapia fish growth and plant productivity in modern aquaponic systems. This research shows the great potential of IoT technology in increasing the efficiency and productivity of aquaponic cultivation, so that it can push the fisheries sector in a more advanced and competitive direction. Therefore, the main conclusion that is expected is that this automation can increase the productivity of ecosystem balance, and can face the challenge of food security and move towards more environmentally friendly solutions, towards effective management in the future.