Information Sciences, Год журнала: 2025, Номер unknown, С. 122321 - 122321
Опубликована: Май 1, 2025
Язык: Английский
Sustainability, Год журнала: 2023, Номер 15(14), С. 11221 - 11221
Опубликована: Июль 19, 2023
Sustainability through digital transformation is essential for contemporary businesses. Embracing sustainability, micro-, small-, and medium-sized enterprises (MSMEs) can gain a competitive advantage, attracting customers investors who share these values. Moreover, incorporating sustainable practices empowers MSMEs to drive innovation, reduce costs, enhance their reputation. This study aims identify how owners or senior managers of initiate project. A systematic literature review was carried out, including 59 publications from 2019 2023. As result, this research identifies the first steps take begin transition by identifying critical organizational capabilities necessary successful transformation, explores technologies that support in sustainability goals, emphasizes significance stakeholders achieving journey. Firstly, should change culture decisions strategies focus on sustainability. Secondly, leading role innovation process allows businesses be more locally globally. Finally, big data technology provide most significant benefit because it will enable analyzing all kinds contributes disruptively decision-making.
Язык: Английский
Процитировано
255
Environmental Technology & Innovation, Год журнала: 2023, Номер 33, С. 103509 - 103509
Опубликована: Дек. 29, 2023
Nowadays the pace of production and consumption is reaching environmentally unsustainable levels. In this regard, great technological advances developed in recent years are postulated as a source opportunities to boost circular economy sustainable development. This wide range possibilities offered by new technologies create more reality has aroused curiosity interest academic world, especially years. The main objective research reveal challenges that arise when incorporating objectives economy. Regarding methodology, study been partially supported using bibliometric techniques. results highlight transformative role technologies, blockchain artificial intelligence, advancing economy, with particular emphasis on community technology integration, ethical considerations, synergies, business models, burgeoning bioeconomy. We conclude promise enhanced resource efficiency, optimized supply chains, innovative improved product lifecycle management, offering profound economic environmental benefits while fostering collaborative innovation. However, these also represent address, such integrating advanced methods, ensuring chain transparency, overcoming skill gap, avoiding data centralization, adapting regulatory frameworks foster equitable growth. These some most important areas for further research, those related development employees' capabilities adaptation frameworks, they understudied gaps.
Язык: Английский
Процитировано
101
Nature Reviews Earth & Environment, Год журнала: 2024, Номер 5(7), С. 504 - 521
Опубликована: Июнь 6, 2024
Effective management of water resources is crucial for global food security and sustainable development. In this Review, we explore the potential benefits challenges associated with treated wastewater (TW) reuse irrigation. Currently, 400 km3 yr−1 generated globally, but <20% treated, that TW, only 2–15% reused irrigation depending on region. The main limitation TW inability current treatment technologies to completely remove all micropollutants contaminants emerging concern, some which have unknown impacts crops, environment health. However, advanced schemes, supported by quality monitoring regulations, can provide a stable supply agricultural production, as demonstrated in regions such USA Israel. Such schemes could potentially serve net energy source, embedded exceeds needs 9 10 times. Agriculturally useful nutrients nitrogen, phosphorus potassium be also recovered reused. act major contributor circular economy development, first steps will funding implementation social acceptance. Treated alleviate imbalances boost production water-scarce regions, thus promoting security. This Review discusses widespread agriculture framework.
Язык: Английский
Процитировано
38
IEEE Internet of Things Journal, Год журнала: 2024, Номер 11(15), С. 25757 - 25770
Опубликована: Апрель 12, 2024
Effective data management schemes have always been the major demand in universal industrial Internet of Things (IoT) systems, especially resource-constrained scenarios. In realistic wastewater treatment process (WTP), only limited monitoring resource can be available due to some digital constraint. Aiming at this practical issue, work explores utilization deep neural network deal with such issue objective situation. Therefore, a learning-based scheme for intelligent control WTP under IoT is proposed paper. Firstly, specific encoding and preprocessing approach developed business scenario. Then, detailed workflow structure applied predict key intermediate parameters which further guide decision. Finally, comprehensive series experiments are conducted on real-world dataset covers range one year. Both efficiency robustness proposal tested by introducing several performance metrics. The results show that it proper prediction effect environment, facilitate following operations.
Язык: Английский
Процитировано
27
Journal of Water Process Engineering, Год журнала: 2024, Номер 63, С. 105486 - 105486
Опубликована: Май 30, 2024
Wastewater treatment plants (WWTPs) play a crucial role in ensuring safe environment by effectively removing contaminants and minimizing pollutant discharges. Compliance with stringent regulations the search for sustainable processes pose new challenges provide opportunities innovative solutions. These solutions include using wastewater as resource to recover value-added by-products, such clean water, renewable energy, nutrients, while optimizing energy consumption reducing operating costs without compromising performance. To drive continuous innovation treatment, integration of advanced technologies robust monitoring control systems is imperative. This review explores advancements automation process within WWTPs. In this context, Internet Things (IoT), cloud computing, big data analytics, artificial intelligence (AI), blockchain, robotics, drones, virtual/augmented reality (VR/AR), digital twin are identified promising tools developing innovative, smart, efficient systems. While these offers many benefits, further research essential optimize their performance cost-effectiveness. A detailed overview current future applications smart provided, emphasizing strengths, limitations, improvements.
Язык: Английский
Процитировано
20
ACS ES&T Water, Год журнала: 2023, Номер 4(3), С. 784 - 804
Опубликована: Авг. 24, 2023
Wastewater treatment companies are facing several challenges related to the optimization of energy efficiency, meeting more restricted water quality standards, and resource recovery potential. Over past decades, computational models have gained recognition as effective tools for addressing some these challenges, contributing economic operational efficiencies wastewater plants (WWTPs). To predict performance WWTPs, numerous deterministic, stochastic, time series-based been developed. Mechanistic models, incorporating physical empirical knowledge, dominant predictive models. However, represent a simplification reality, resulting in model structure uncertainty constant need calibration. With increasing amount available data, data-driven becoming attractive. The implementation can revolutionize way manage WWTPs by permitting development digital twins process simulation (near) real-time. In is not explicitly specified but instead determined searching relationships data. Thus, main objective present review discuss machine learning prediction WWTP effluent characteristics inflows well anomaly detection studies consumption WWTPs. Furthermore, an overview considering merging both mechanistic hybrid presented promising approach. A critical assessment gaps future directions on mathematical modeling processes also presented, focusing topics such explainability use Transfer Learning processes.
Язык: Английский
Процитировано
40
Sustainable Cities and Society, Год журнала: 2023, Номер 94, С. 104541 - 104541
Опубликована: Март 17, 2023
Язык: Английский
Процитировано
30
The Science of The Total Environment, Год журнала: 2024, Номер 944, С. 173999 - 173999
Опубликована: Июнь 13, 2024
Membrane technologies have become proficient alternatives for advanced wastewater treatment, ensuring high contaminant removal and sustainable resource recovery. Despite significant progress, ongoing research efforts aim to further optimize treatment performance. Among the challenges faced, membrane fouling persists as a relevant obstacle in technologies, necessitating development of more effective mitigation strategies. Mathematical models, widely employed predicting performance, generally exhibit low accuracy suffer from uncertainties due complex variable nature wastewater. To overcome these limitations, numerous studies proposed artificial intelligence (AI) modeling accurately predict technologies' performance mechanisms. This approach aims provide simulations predictions, thereby enhancing process control, optimization, intensification. literature review explores recent advancements membrane-based processes through AI models. The analysis highlights enormous potential this field efficiency technologies. role defining optimal operating conditions, developing strategies mitigation, novel improving fabrication techniques is discussed. These enhanced optimization control driven by ensure improved effluent quality, optimized consumption, minimized costs. contribution cutting-edge paradigm shift toward examined. Finally, outlines future perspectives, emphasizing that require attention current limitations hindering integration plants.
Язык: Английский
Процитировано
17
The Science of The Total Environment, Год журнала: 2024, Номер 915, С. 169903 - 169903
Опубликована: Янв. 8, 2024
Wastewater treatment plant decision makers face stricter regulations regarding human health protection, environmental preservation, and emissions reduction, meaning they must improve process sustainability circularity, whilst maintaining economic performance. This creates complex multi-objective problems when operating selecting technologies to meet these demands, resulting in the development of many support systems for water sector. European Commission publications highlight their ambition greater levels sustainability, which system implementation should align with be successful this region. Following review 57 wastewater systems, main function multi-criteria decision-making tools are technology selection optimisation operation. A large contrast aims is found, as clearly define goals indicators used, procedures often use vague language making it difficult connect selected resultant outcomes. Several recommendations made usage, such more rigorous indicator protocols including participatory approaches expansion sets, well structured investigation results sensitivity or uncertainty analysis, error quantification.
Язык: Английский
Процитировано
11
Environmental Chemistry Letters, Год журнала: 2024, Номер 22(5), С. 2293 - 2318
Опубликована: Май 21, 2024
Abstract The access to clean and drinkable water is becoming one of the major health issues because most natural waters are now polluted in context rapid industrialization urbanization. Moreover, pollutants such as antibiotics escape conventional wastewater treatments thus discharged ecosystems, requiring advanced techniques for treatment. Here we review use artificial intelligence machine learning optimize pharmaceutical treatment systems, with focus on quality, disinfection, renewable energy, biological treatment, blockchain technology, algorithms, big data, cyber-physical automated smart grid power distribution networks. Artificial allows monitoring contaminants, facilitating data analysis, diagnosing easing autonomous decision-making, predicting process parameters. We discuss advances technical reliability, energy resources management, cyber-resilience, security functionalities, robust multidimensional performance platform distributed consortium, stabilization abnormal fluctuations quality
Язык: Английский
Процитировано
11