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Participatory wireless sensor networks (PWSN) is an emerging paradigm that leverages existing sensing and communication infrastructures for the sensing task. Various environmental phenomenon – P monitoring applications dealing with noise pollution, road traffic, requiring spatio-temporal data samples of P (to capture its variations and its profile construction) in the region of interest – can be enabled using PWSN. Because of irregular distribution and uncontrollable mobility of people (with mobile phones), and their willingness to participate, complete spatio-temporal (CST) coverage of P may not be ensured. Therefore, unobserved data values must be estimated for CST profile construction of P and presented in this paper.

In this paper, the estimation of these missing data samples both in spatial and temporal dimension is being discussed, and the paper shows that non-parametric technique – Kernel Regression – provides better estimation compared to parametric regression techniques in PWSN context for spatial estimation. Furthermore, the preliminary results for estimation in temporal dimension have been provided. The deterministic and stochastic approaches toward estimation in the context of PWSN have also been discussed.

For the task of spatial profile reconstruction, it is shown that non-parametric estimation technique (kernel regression) gives a better estimation of the unobserved data points. In case of temporal estimation, few preliminary techniques have been studied and have shown that further investigations are required to find out best estimation technique(s) which may approximate the missing observations (temporally) with considerably less error.

This study addresses the environmental informatics issues related to deterministic and stochastic approaches using PWSN.

This study aims to provide a comprehensive framework for the study of indoor air quality (IAQ) in hospitality premises. The goal is to identify the drivers of air pollution, both at the exogenous and endogenous level, to generate insights for facility managers.

The complexity of hospitality premises requires an integrated approach to properly investigate IAQ. The authors develop an overarching framework encompassing a monitoring method, based on real-time sensors, a technological standard and a set of statistical analyses for the assessment of both IAQ performance and drivers, based on correlation analyses, analysis of variance and multivariate regressions.

The findings suggest that the main drivers of IAQ differ depending on the area monitored: areas in contact with the outdoors or with high ventilation rates, such as halls, are affected by outdoor air quality more than guestrooms or fitness areas, where human activities are the main sources of contamination.

The results suggest that the integration of IAQ indicators into control dashboards would support management decisions, both in defining protocols to support resilience of the sector in a postpandemic world and in directing investments on the premises. This would also address guests’ pressing demands for a broader approach to cleanliness and safety and support their satisfaction and intention to return.

To the best of the authors’ knowledge, this is the first study developing a comprehensive framework to systematically address IAQ and its drivers, based on a standard and real-time monitoring. The framework has been applied across the longest period of monitoring for a hospitality premise thus far and over an entire hotel facility.

The self-cleaning properties of nanostructured titanium dioxide facade coatings are useful in Singapore's tropical climate. However, its potential maintenance issues need to be determined right at the design stage. The purpose of this paper is to highlight the development of the design for maintainability tool which is a multicriteria design decision score sheet that evaluates the maintainability potential of nano-facade coating applications on high-rise façades with concrete and stonemasonry finishes and curtain walls.

Quantitative methods (expert and practitioner surveys) are conducted in this research study. Analytic hierarchy process (AHP) and sensitivity analysis were used to develop a robust Design for Maintainability tool.

Safety measures indicator received the highest weighted score by experts, while the maximizing performance, minimizing risk, minimizing negative environmental impact and minimizing consumption of matter and energy were the top ranking main criteria by both experts and practitioners. The top ranked design for maintainability sub-criteria identified by practitioners and experts were risk management, maintenance considerations, climatic conditions, safety measures, lifecycle cost and maintenance access, sun's path, rainfall intensity, biological growth measures and building age profile.

Most researches on the maintainability of nano-façade coatings uses experimentation to test the durability of nano-façade coatings, while this study focuses on design based empirical data such as establishing and ranking the list of design for maintainability criteria or indicators to minimize future defects and maintenance issues. The design for maintainability tool contributes to the maintainability of nano-façade coatings leading to maximizing its performance while minimizing cost, risks, resource consumption and negative environmental impact.

The purpose of this study is to investigate the pivotal role of environmental innovations in driving sustainability practices within medium and large manufacturing firms operating in Uganda.

Using a cross-sectional and quantitative methodology, data were collected through a questionnaire survey involving 208 manufacturing companies. The smart partial least squares path modelling technique was used for the analysis.

The analysis unveils significant and positive associations. Specifically, product innovation exhibits a robust and affirmative relationship with sustainability practices. Similarly, the correlation between process innovation and sustainability practices emerges as statistically significant. Moreover, the findings underscore the noteworthy and constructive predictive influence of environmental innovation on sustainability practices.

These empirical results present substantial implications for theoretical frameworks and practical applications. From a policy perspective, the findings emphasise the importance of incentivising eco product and eco process innovations as potential drivers of eco-friendly practices. On the managerial front, strategic resource allocation and the adoption of integrated environmental innovation strategies are advocated, with the ultimate goal of enhancing sustainable business approaches within Uganda’s manufacturing subsector.

To the best of the authors' knowledge, this study represents the inaugural attempt to investigate the role of environmental innovations in elucidating sustainability practices within a least developed country. Notably, while all dimensions demonstrate significance, it is noteworthy that product innovation emerges as the more substantial contributor to the promotion of sustainability practices.

The purpose of this paper is to use the case of an international luxury hotel chain in Hong Kong to illustrate general environmentally-friendly practices in housekeeping. Six in-depth interviews were conducted with the housekeeping department staff to evaluate the effectiveness of the Hotel’s environmental sustainability practices by analysing their benefits and limitations. Results reveal that all informants acknowledged the environmental sustainability strategies adopted by the Hotel, which can benefit stakeholders. Despite multiple green practices in hotel housekeeping, several strategies may not be as significant as expected with misaligned expectations from the management and the actual practices may create excessive workload for frontline room attendants with a lack of policy enforcement and supportive policies. Therefore, hotels should keep a mutual communication between the management and frontline employees prior to conducting environmentally- and employee-friendly practices. Given the labour-intensive nature of the hotel industry, the housekeeping department should ensure employment equality policy is in place with adequate environmentally friendly support for employees.

Sustainable building design suffers from a lack of reliable life cycle data. The purpose of this paper is to compare life cycle costs of sustainable building projects, examine the magnitude of various cost drivers and discuss the implications of an emerging shift in cost drivers.

This paper is based on data from 21 office buildings certified in Denmark according to the sustainable certification scheme DGNB.

The paper supports previous findings that construction costs and running costs each roughly make up half of the life cycle costs over a 50-year period. More surprising is the finding that the life cycle costs for cleaning are approximately twice as high as the supply costs for energy and water.

The data set is based on actual construction costs of office buildings constructed in 2013-2017. Although all running costs are calculated rather than measured, they are based on a more detailed, specific and industry-supported set of calculation assumptions than is usual for life cycle costing studies because of extensive collaborative work in a number of concomitant national research and development projects.

Authorities, clients and building professionals heavily emphasise energy-saving measures in new Danish buildings. The paper suggests redirecting this effort towards other more prominent cost drivers like cleaning and technical installations.

This paper provides a notable contribution to the academic understanding of the significance of different cost drivers as well as the practical implementation of life cycle costing.

The first step toward developing an automated construction workers performance monitoring system is to initially establish a complete and competent activity recognition solution, which is still lacking. This study aims to propose a novel approach of using labor physiological data collected through wearable sensors as means of remote and automatic activity recognition.

A pilot study is conducted against three pre-fabrication stone construction workers throughout three full working shifts to test the ability of automatically recognizing the type of activities they perform in-site through their lively measured physiological signals (i.e. blood volume pulse, respiration rate, heart rate, galvanic skin response and skin temperature). The physiological data are broadcasted from wearable sensors to a tablet application developed for this particular purpose, and are therefore used to train and assess the performance of various machine-learning classifiers.

A promising result of up to 88% accuracy level for activity recognition was achieved by using an artificial neural network classifier. Nonetheless, special care needs to be taken for some activities that evoke similar physiological patterns. It is expected that blending this method with other currently developed camera-based or kinetic-based methods would yield higher activity recognition accuracy levels.

The proposed method complements previously proposed labor tracking methods that focused on monitoring labor trajectories and postures, by using additional rich source of information from labors physiology, for real-time and remote activity recognition. Ultimately, this paves for an automated and comprehensive solution with which construction managers could monitor, control and collect rich real-time data about workers performance remotely.

In this paper, a high-frequency radar test system was used to collect the data of clean ballast bed and fouled ballast bed of ballasted tracks, respectively, for a quantitative evaluation of the condition of railway ballast bed.

Based on original radar signals, the time–frequency characteristics of radar signals were analyzed, five ballast bed condition characteristic indexes were proposed, including the frequency domain integral area, scanning area, number of intersections with the time axis, number of time-domain inflection points and amplitude envelope obtained by Hilbert transform, and the effectiveness and sensitivity of the indexes were analyzed.

The thickness of ballast bed tested at the sleep bottom by high-frequency radar is up to 55 cm, which meets the requirements of ballast bed detection. Compared with clean ballast bed, the values of the five indexes of fouled ballast bed are larger, and the five indexes could effectively show the condition of the ballast bed. The computational efficiency of amplitude envelope obtained by Hilbert transform is 140 s·km⁻¹, and the computational efficiency of other indexes is 5 s·km⁻¹. The amplitude envelopes obtained by Hilbert transform in the subgrade sections and tunnel sections are the most sensitive, followed by scanning area. The number of intersections with the time axis in the bridge sections was the most sensitive, followed by the scanning area. The scanning area can adapt to different substructures such as subgrade, bridges and tunnels, with high comprehensive sensitivity.

The research can provide appropriate characteristic indexes from the high-frequency radar original signal to quantitatively evaluate ballast bed condition under different substructures.

This study aims to assess the response of the Association of Southeast Asian Nations (ASEAN) to cleaner production and environmental sustainability, with a specific focus on identifying the leading countries and research networks driving these efforts.

A benchmarking academic journal was chosen, and the journal’s archive was comprehensively examined. To construct the data set, a conventional keyword search technique was applied in February 2023 to filter for ASEAN affiliations. The study used hybrid bibliometric analyses and multi-criteria decision analysis (MCDA) to analyze the collected data and address the research purpose.

The data analysis revealed a rising research trend, particularly after 2014. Malaysia had the most publications, followed by Thailand and Singapore, and their publications had the most cumulative citations among ASEAN countries. Research collaborations between Malaysia, Thailand and Singapore were frequent, but participation from other countries was low. The research topics on which ASEAN members focused were also identified, but it became apparent that there was little coordination. A scant few collaborations involving more than two countries were observed; thus, the MCDA analysis concluded that research leadership was absent in ASEAN countries.

This study contributes insights to the existing literature and offers a valuable overview of the research direction and collaboration status of cleaner production and environmental sustainability in the ASEAN region, thus benefiting policymakers. Additionally, this study introduces a novel approach combining bibliometrics analysis with MCDA to assess research collaboration, thus providing a novel methodology for future research policy evaluations.

The study aims to determine the impact of sustainable manufacturing on environmental performance through government regulation and eco-innovation in Indonesian small and medium-sized enterprises (SMEs).

The results indicate sustainable manufacturing plays a significant role in SMEs' environmental performance and regulations, and eco-innovation can moderate it. It also reveals that government regulation has a positive and significant effect on environmental performance. Moreover, eco-innovation has a positive and significant effect on environmental performance.

The findings of this study indicate that SMEs can embrace sustainable manufacturing practices and achieve their long-term sustainability goals by adhering to regulations, collaborating with stakeholders and implementing eco-friendly innovations.

This research uncovers ground-breaking perspectives on the evolution of scientific knowledge about the impact of eco-innovation, regulatory measures and sustainable manufacturing practices on the environmental performance of SMEs.