Housing Solutions Research Articles

Sustainability of Temporary Housing in Post-Disaster Scenarios: A Requirement-Based Design Strategy

Disasters, whether natural or man-made, pose inevitable global challenges. Events such as COVID-19, earthquakes, extreme climatic conditions, and conflicts underscore the urgent demand for effective temporary housing solutions. These temporary housing units (THUs) serve as an aid in assisting displaced people to rebuild their lives as the recovery process unfolds. However, numerous temporary housing units present environmental, economic, and social issues that hinder their sustainability. This paper investigates the underlying causes of these issues, defines the essential requirements that temporary housing units must meet, and proposes an initial design to fulfill these requirements. The methodology comprises three key phases: case study analysis, requirement identification, and the integration of these requirements into the design process. The main findings highlight that the construction of sustainable temporary housing units necessitates a meticulous consideration of various parameters to achieve a balanced equilibrium between economic, social, and environmental impacts. Possible future research directions are emphasized, including the use of digital tools and BIM models to promote the adoption of circular economy practices and the validation of the design solution through value analysis. Possible improvements in the user’s well-being are also taken into consideration.

Idobata-Nagaya: a community housing solution for socially isolated older adults following the great East Japan earthquake.

Following the Great East Japan Earthquake, the living environment of socially isolated older adults has become a pressing concern. In response, Nagaya, a collective housing program, was established in Soma City, Fukushima, Japan to address social isolation among older adults and support their long-term health. This study aimed to identify characteristics of individuals in Nagaya and examine the sustainability of this initiative. We conducted a retrospective analysis of residents who were relocated to Nagaya, emphasizing their characteristics, the continuity of their stay in Nagaya, and their care certification levels, using data up to December 31, 2022. We employed Kaplan-Meier curves to analyze the duration for which residents continued to reside in Nagaya and the time leading up to the requiring care-level certification. Of 65 people who moved to Nagaya after the disaster, 30 people (46.2%) continued to live there, 21 (32.3%) died during their stay, and 14 (21.5%) moved out. The overall duration of occupancy averaged 6.39 years (SD 3.83 years). The proportion of requiring care-level certification occurrences per person-year was 0.0577 for those without care certification and 0.3358 for those with requiring support level at the time of moving in. In summary, Nagaya-style communal housing may offer suitable living environments for older adults with diverse needs during disasters and serve as a valuable tool for developing public policies in aging societies.

INVESTIGATING THE INFLUENCE OF HOMEBUYERS’ SOCIODEMOGRAPHIC FACTORS ON PREFERENCES OF SUSTAINABLE AFFORDABLE HOUSING

Low- and middle-income groups face difficulties in homeownership because of the urbanisation and rising living standards, in which they rely heavily on the government’s housing provision. Yet, affordable housing provided in Malaysia has been repeatedly criticised as it is not up to homebuyers’ expectations and is not supported to reach sustainable goals. Hence, this research aims to investigate the influence of the sociodemographic background of the homebuyers on their preferences for sustainable affordable housing in Malaysia. The questionnaire was designed and responses were obtained from 316 low- and middle-income homebuyers. Spearman rank correlation and ordinal regression were used to investigate the association between homebuyers’ sociodemographic characteristics and their preference for sustainable affordable housing. Spearman correlation analysis revealed that gender, generation, marital status and monthly income were significantly correlated with sustainability criteria. The ordinal regression model reflected that stronger preferences for sustainable affordable housing were shown among female homebuyers, Gen Y and Baby Boomer homebuyers and married ones. The research findings close the gap between users (homebuyers) and the providers (developer/government) in the provision of affordable housing. Developers and the local authorities can provide sustainable affordable housing solutions that suit the needs of different homebuyers.

Land use changes and residential area expansion in South Tangerang City, Indonesia

PurposeThe purpose of the study is to analyze changes in land use, specifically residential area expansion, in South Tangerang City and identify the factors that influence land use change.Design/methodology/approachThe study used remote sensing methods in ArcGIS 10.8 for data analysis and processing, including spatial analysis and identification of land use changes. The study analyzed satellite images from 2010 and 2020 to identify changes in land use in South Tangerang City over the ten-year period.FindingsThe study found that the most significant land use changes in South Tangerang City between 2010 and 2020 were the reduction of mixed plantation area and the expansion of residential areas. The study identified the development of small townships by private developers as the main factor that influenced land use change in South Tangerang City.Research limitations/implicationsThe study has several limitations, including a focus on only one aspect of land use change (i.e. residential area expansion), limited scope of the study area (South Tangerang City) and a reliance on remote sensing methods for data analysis.Practical implicationsThe findings of the study can be used by policymakers and city planners to develop sustainable land use planning strategies that balance the need for urban development with environmental and social concerns. By understanding the factors that drive land use changes in South Tangerang City, policymakers can develop policies that encourage sustainable urban growth and development while preserving natural resources and protecting the environment.Social implicationsThe study has social implications as the expansion of residential areas in South Tangerang City indicates a growing demand for housing in the area. The study highlights the importance of developing affordable and sustainable housing solutions to meet the needs of the growing population in South Tangerang City. Additionally, the study emphasizes the importance of understanding the social and economic factors that drive land use change and their implications for the well-being of local communities.Originality/valueThe residential area development in South Tangerang City is driven by private developers who make small independent cities that have all facilities in one area. These small cities attract people to reside and also drive high population growth in South Tangerang City, considering it is a buffer city of Jakarta that has good infrastructure development.

Assessment of Current Smart House Solutions: The Case of Portugal

The world is facing many challenges to keep up with growing energy demand and greenhouse gas and pollutant emissions. A possible solution is to integrate renewable energy sources (RESs) into residences and create energy management systems (EMSs) that reduce consumption and relieve the main grid in critical hours. This paper is focused on analyzing different EMSs using solar photovoltaic (PV) modules and three energy storage systems (ESSs) to increase savings without affecting the user’s needs, with thirty-three power consumption profiles and three energy tariffs over a 25-year investment to compare which solution presents the best economic result in each of the 297 analyzed scenarios. The results show that the higher the overall daily consumption values, the greater the profits for all EMSs. The lowest demand profiles lead to the best self-consumption and self-sufficiency results. PV-only systems with a tri-hourly tariff have the best overall results. In the case of battery operation, each case should be carefully analyzed in order to choose the correct technologies and tariff. The results also allowed us to verify that even though having more PV modules generates more energy, it can make a project less economically desirable.

Reviewing the affordability and adequacy of affordable housing in urban India: impact of the covid-19 pandemic

PurposeHousing policies in India (last modified in 2017) define “affordable housing” on three main parameters – income of the target group, dwelling unit size and house price to income ratio. The Covid-19 pandemic has questioned the robustness of the defining parameters of affordable housing. This paper aims to study the impact of Covid-19 pandemic on housing affordability and adequacy for the urban poor and highlights how one pandemic has directly challenged the practicality of the affordable housing criteria in urban India.Design/methodology/approachThe study is based on a pilot test conducted through interviews with the consumer group. Furthermore, the affordable housing policies of urban India were studied in conjunction with the pandemic guidelines laid down by the World Health Organization. The consumer responses were analyzed in relation to the policies and guidelines to arrive at the inferences. The secondary case examples of the Dharavi slums in Mumbai and the Savda Ghevra slum resettlement colony in Delhi, along with the findings of the primary survey in the economically weaker section category, are used to formulate the conclusions.FindingsThe pilot test conducted for the target consumer group clearly indicates that (i) the pandemic has severely affected the housing purchase capacity of the target consumer, thereby questioning the “affordability” of housing; (ii) proposed housing solutions are inadequate to enable livability, thereby questioning the “adequacy” of housing; and (iii) proposed housing solutions are inept to accommodate pandemic protocols. The Covid-19 pandemic and the conditions it imposed on the built environment clearly highlight the inadequacy of affordable housing parameters being followed in urban India.Research limitations/implicationsFurther research may be conducted on global best practices in housing, which may advise the housing policies in India.Practical implicationsThe study suggests key areas that need intervention and modification to make the housing policies more robust and effective.Social implicationsThe study explores the social sustainability aspects of housing, which are often considered secondary in policies.Originality/valueBecause housing has a direct bearing on the physical, social and mental well-being of society, it is imperative to find housing solutions that are safe and resilient for a sustainable future. This paper is an original attempt by the author to question and highlight how the current affordable housing solutions adopted in urban India will continue to fail under any external adverse conditions unless modifications are considered in the existing housing parameters.

Pandemic housing policies: mitigation strategies and protection of rights

ABSTRACT A housing crisis was already plaguing communities long before the COVID-19 pandemic began, further accelerating the need for effective housing solutions. Building on a critical examination of government housing policy responses to support households keep their homes during the pandemic, this article reviews and documents the housing policies implemented in the context of the health crisis to protect vulnerable populations, in addition to some of the gaps found in those policies. Using data from OECD countries, the article explores the key actions implemented as a springboard to argue that a) governments were only able to swiftly enact those policies because they were temporary measures in response to a time-limited crisis, and b) that those Covid-related pandemic measures fail to address the deep-rooted structural inadequacies of housing systems. While demonstrating the added value and possibilities of such housing solutions, the study further argues that pandemic-oriented housing solutions could provide an opportunity to reconsider housing objectives that some governments deemed impossible or impracticable before the COVID-19 health crisis. The study suggests that countries should champion investments in affordable housing and convert their impetus for short-term coronavirus changes into fairer, more inclusive and longer-term housing protections.

The Advantages of Using Artificial Intelligence in Urban Planning – A Review of Literature

Urban planning plays a crucial role in shaping communities for the future, analyzing their strengths and weaknesses, and proposing improvement solutions.This systematic literature review process used in this study ensured the inclusion of a wide range of sources, providing a comprehensive overview of the advantages of using artificial intelligence in urban planning. After a careful review of the literature, it is found that artificial intelligence is primarily used to enhance efficiency in urban planning processes, contributing to sustainability. The potential for future challenges has accelerated the adoption of artificial intelligence in urban planning by emphasizing the need for resilient, technology-driven cities. It supports more efficient urban design by automating tasks through generative design software, which subdivides plots and applies housing solutions. Artificial intelligence's role expands to multiple areas within the urban planning obligations of a city, including transportation, environment, waste management, education, healthcare, agriculture, risk management, and security. It guides urban planners by improving analytical models for understanding future physical and social community conditions. Artificial intelligence empowers planners to explore new data collection and analysis methods for predicting urban behavior, saving time and resources. It addresses climate change challenges by supporting transportation, waste management, and water use applications. Artificial intelligence technologies continue to advance, urban planning stands to benefit from increased efficiency, data-driven decision-making, and the creation of more sustainable, resilient cities. Urban planners must adapt themselves by acquiring the necessary skills to ensure successful city planning for the future. Overall, Artificial intelligence is contributing heavily to achieving sustainability by integrating past practices, trends, and new AI-based models.

Urban, Environmental and Habitability Parameters for Social Housing

Purpose: The purpose of this study is to propose a set of parameters for urban, environmental, and habitability impacts for the feasibility analysis of social housing projects. Theoretical framework: Given the historical housing deficit, the large scale of social housing segment has been challenging managers in terms of environmental (volume of inputs, energy, waste), economic (high investment), and social (urban relations) impacts. Thus, efficiency in the performance of Social Housing Projects is a relevant aspect, regarding the importance that housing represents in users’ lives. Method/design/approach: The research strategy used was case studies, using 12 social housing projects built in Rio de Janeiro and Porto Alegre. The parameters analyzed refer to urban, environmental and habitability impact, based on data collected in loco, seeking to identify the main variables that influence each one, categorized as greater, medium or smaller influence. Results and conclusion: The variables with the most significant impact were: (i) mobility, access to opportunities, degree of localism, and social networks (urban parameters); (ii) index of compactness of the buildings and place of manufacture of the materials (environmental parameters); (iii) bioclimatic zone, facade color, window size, architectural type, and (iv) construction system (living parameters). Research implications: The proposed parameters may be helpful to public authorities (funders/inspectors), designers/builders (executors), and academics (theoretical/technical support) as a guide to more efficient social housing solutions involving the construction of programs, guidelines for public notices, parameters assessment, among others. Originality/value: The study contributes to the existing literature by encompassing a systemic approach to EHIS, being propositional through parameters that integrate issues related to construction and urban performance.

The permanent regime of temporary solutions: Housing of forced migrants in Europe as a policy challenge

Periods of forced migration to and in Europe have been common in the past decade and show no expectation of stalling due to ongoing armed conflicts, global inequalities and the adverse effects of climate change. Nevertheless, the provision of accommodation for asylum seekers and refugees continues to depend on temporary, ad hoc solutions. In the context of housing financialisation and shortage of affordable housing across European cities, this decreases opportunities for integration and securing other needs, such as jobs, language acquisition and childcare, but increases the risk of refugee homelessness and social exclusion. Based on cross-national Urban Living Labs exchanges in Leipzig, Riga, Lund, Helsingborg and Vienna, this commentary argues for a European agenda for long-term housing solutions for forced migrants in the arrival and settling phases that tackle issues from discrimination to access, to belonging. Importantly, creating long-term housing solutions for refugees would benefit whole housing systems as instruments of social inclusion.

Exploring the Affordable Housing Solutions for the Resettlement Projects of Padma Bridge

The construction of Padma Bridge in Bangladesh has necessitated the resettlement of displaced residents, highlighting the need for affordable and sustainable housing solutions aligned with Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure), 10 (Reduce inequality), and 11 (Sustainable Cities and Communities). This study aims to engage undergraduate architecture students in a design studio exercise to develop innovative housing models for resettlement projects, addressing displaced communities' social, economic, and environmental challenges. A multi-criteria decision analysis (MCDA) framework is introduced, integrating stakeholder data. In the design studio, students explore housing alternatives and concentrate on community-driven cooperative housing, assessing their effectiveness, feasibility, and sustainability using the MCDA framework. The exercise produces a range of housing solutions that balance affordability, sustainability, and community-centric design. Students demonstrate the potential of novel approaches to address the complex challenges displaced communities face and contribute to equitable development in Bangladesh. Engaging architecture students in developing affordable housing solutions provides valuable insights for policymakers and stakeholders in resettlement. The study emphasizes the need for holistic, participatory approaches and highlights the role of innovative, sustainable housing models in enhancing the quality of life for those affected by the Padma Bridge project, aligning with the SDGs.

Functional and Psychosocial Profile of Older People Living in Nursing Homes: Findings from the European Survey of Health, Ageing and Retirement in Europe (SHARE).

This paper is based on results from the Survey of Health, Ageing and Retirement in Europe (SHARE), exploring many aspects (health, economic situation and welfare) of the European population aged 50+. Differently from many other international studies, SHARE includes persons living in nursing homes or residential care facilities as part of its sample. The aim of this paper is to provide a socio-demographic, functional and psychosocial snapshot of older residents in nursing homes in Europe. This paper uses data from SHARE Wave 8/2020, carried out in 27 European countries. A quantitative/descriptive approach explores the prevalence of older people aged 65+ living in residential facilities as mapped by the SHARE survey across Europe, with regard to associated dimensions, i.e., socio-demographic, family relationship, perceived health/main diseases, functional and psychological status. These show that older residents live mainly in Central and Northern Europe, are aged 80+, female and widowed. A small social network (SN) size is often reported. Health is perceived, above all, as being fair-poor, and the presence of long-term illness is high, with several chronic health conditions and functional limitations. The reported quality of life (QoL) is low for most respondents, with moderate-low satisfaction with life. The analysis depicts a profile of seniors needing residential care in Europe, and provides useful insights for policymakers, to better sustain this frail population group, and to allow and improve access to high-quality long-term care (LTC) in Europe. Our findings could also be of help to train health professionals, and potentially drive the research towards the exploration of new housing solutions for seniors. This would in turn contribute to the effective implementation of European initiatives to strengthen LTC systems.

TOD in regional urban growth boundaries (UGBs): A case of transit adjacent development or a strategic housing solution?

The Green Belt in England is probably the most longstanding and internationally recognised Urban Growth Boundary (UBG). However, developers, think tanks and academics often accuse UGB's of being the leading cause of the housing affordability problems around the world and articulate an alternative vision of Transit-Oriented Development (TOD). This paper, based upon a regional case study of the West Midlands and 74 interviews with planners and planning stakeholders, argues that the debate around TOD in the Green Belt needs to be more cognisant of regional geographical variation in public transport provision. Moreover, drawing upon the views of planners who play a key a role in allocating land for development, the paper underlines that decisions regarding TOD need to made strategically as reflecting the policy's purpose as a regional growth management policy. Reflecting on the broader academic literature, it highlights the need for greater strategic integration of transport and land-use planning alongside reviving strategic planning to evaluate various spatial blueprints for urban growth management. The paper has broader relevance to international debates about the feasibility and potential of TOD, especially in addressing housing affordability problems around the world.

MODERN ARCHITECTURAL APPROACHES TO SMART CITIES AND EDUCATIONAL FACILITIES

Introduction: This article aims to provide readers with an overview of significant modern architectural approaches to creating sustainable smart city models. Different architectural approaches have piqued the interest of many researchers that study ancient and modern buildings, specifically their characteristics and execution methods. Purpose of the study: Interest toward smart architecture has grown due to the extensive development of technology and its integration into all aspects of human and city life, including the learning environment, the psychological effect of various spaces, and environmental impact. Methods: Architects, designers, engineers, and psychologists alike must consider these key developments and choose approaches to spaces and buildings that properly reflect the smart building philosophy. Many case studies have been adopted in the current investigation. Results: Over the recent years, due to the increasing strain of real estate demands, which led to overcrowding in cities, the need to find the most suitable housing solutions has emerged as a key problem. Architects and researchers are considering the best modern architectural approaches to building a sustainable model for smart cities.

Predicting Passivhaus certification of dwellings using machine learning: A comparative analysis of logistic regression and gradient boosting decision trees

Passivhaus has gained recognition as a reliable solution for low-energy residential housing. However, existing studies lack comprehensive quantitative analysis of real-life cases, restricting the availability of evidence and experience from certified buildings. This study addresses this gap by examining the relationship between characteristics of certified passive houses and their energy performance. The objective is to establish dependable statistical models and best practices for early design stages of passive houses. The study analyzes a significant number of certified cases (n = 785) in residential settings situated in two climate zones: Temperate, no dry season, warm summer (n = 328, 41.78%) and Cold, no dry season, warm summer (n = 457, 58.22%). To assess whether residential buildings meet passive house energy standards, models using logistic regression and gradient boosting decision trees were developed employing three boosting methods: XGBoost, LightGBM, and CatBoost. Results reveal that CatBoost (F1 = 0.73, Logloss = 0.63, AUC = 0.78, Brier = 0.22) outperforms logistic regression (F1 = 0.72, Logloss = 0.62, AUC = 0.72, Brier = 0.22) in terms of accuracy. Additionally, LightGBM (F1 = 0.79, Logloss = 0.58, AUC = 0.75, Brier = 0.20) exhibits superior predictive calibration. This study indicates that external wall, floor slab, and roof thermal performance are crucial factors for meeting passive house standards (P-value = 0.0046). The research also discusses innovative practices and technologies derived from the certified cases. Overall, this study provides valuable insights for certification systems and early design strategies.

Exploring the Challenges Faced by the Urban Squatter Dwellers in Sentul, Kuala Lumpur, Malaysia

Malaysia has experienced rapid urbanization, leading to congestion and a shortage of adequate housing. For those who cannot afford housing due to the high prices of houses, such as marginalized and low-income groups, squatting becomes an alternative for viable housing solutions. Many have moved into urban squatter zones in search of alternate housing. Drawing on Malaysia as a case study, this study explores the challenges urban squatter dwellers face and how it affects their well-being. This study used Participatory Action Research (PAR) and Delphi Techniques to conduct in-depth interviews with fourteen key informants in Kuala Lumpur. It analyzed the results using the thematic analysis method. Findings revealed that they faced challenges associated with social issues, housing quality, housing environment, and finances. These challenges have affected their safety, comfort, social relationships, and health. It is suggested that the government should adequately design inclusive policies and programs to resolve this predicament and enhance these dwellers’ quality of life. Since studies on urban squatters in Malaysia are scarce, this study provides insight into the country’s urban poverty problem. Furthermore, the findings can be applied to other developing countries with characteristics like Malaysia.

Local Housing Strategy: Analysis of Importance and Implementation in Machico Municipality, Madeira

This article presents a detailed analysis of the local housing strategies (ELH) in the Municipality of Machico, Madeira, examining the diagnosis of housing needs, proposed solutions, and projected goals for the future. In addition to addressing the rehabilitation of private and public housing and the increase in housing supply, the study also explores how ELH relate to the new generation of housing policies and the public support program for promoting housing solutions for vulnerable people. It is important to note that the implementation of ELH in Machico also has a positive impact on the local landscape and climate resilience, promoting the conservation of important forest areas for the production and management of natural resources.

Innovative housing models that reflect the needs of contemporary society. (Post-pandemic context)

This article is concerned with understanding the need for housing in the context of the Covid-19 pandemic and suggesting alternatives to provide solutions for housing in a demanding post-pandemic society and a new lifestyle. Since this pandemic hit the world, the issues revealed tackled primarily general societal health, followed by social distancing, change of transportation concepts, and a new remote work model within the housing unit; putting into a tangible discussion, the overall quality of housing. An emergent need to re-address a new concept for housing, sustaining the actual socio- economic model of living, is frequently being discussed between academics alternating between provision for flexible internal spaces, innovative and resilient houses as well as re- adaptations. In this context of global societal changes, ‘The Housing Unit’, has been positioned under pressure to meet the extra needs of the inhabitants, like better indoor physical comfort and air quality, natural light and ventilation, wider spaces, and flexible interiors, needs which were previously addressed in the outdoor environment. Whiles the impact of the pandemic in regard to housing as the primary unit responsible for the overall quality of life imposes researchers and different professionals in design fields to attend to and forecast changes within the housing as the primary “nucleus” driving the general health and quality of life for the citizens; the situation challenged every component of the urban environment, including the uses of public space, public transportation and movement within the city, which already seeks to be redefined. This research is conducted during a two-week workshop, in the framework of the doctoral program in Architecture and Urban Planning, concerning the context Northern Albanian Region of Lezha, with the participation of the students: Rine Zogiani, Nicola Talamonti, Elena Verzella, Luca Lanzoni, Bianka Madhi,, Armela Lamaj. The results of the workshop, after a thorough investigation of existing housing typologies, the relation of public spaces with residential buildings, and other aspects like sustainability, through the objective of providing innovative housing solutions. generated variable models of housing in two main directions: a) adaptations of existing housing units; and b) new proposals for contemporary, post-pandemic housing. The proposals integrate the use of near public space and the incorporation of auto-sufficient buildings concepts.

Housing Vacancy Outlined with Delphi Survey. Contributions of Participatory Research to a Just Transformation Process on Trial

Rising housing prices, associated supply gaps and displacement processes have revived the “housing issue” in Germany. This is particularly true for certain social groups socially marginalized by high competition in the housing market. The participatory action research study “Wohnungsleerstand wandeln!”(WohL) - “Worthy places from un-used spaces” examines the coexistence of housing scarcity and housing abundance in a district of the Munich metropolitan area. The goal is to use a participatory multi-method design, including a two-stage qualitative Delphi Survey, to find tailored solutions for the housing situation in each community. The Delphi method was used to reflect the diversity of perspectives in housing as well as the principles of participatory action research such as participation in research, proximity to the field, and capacity building through mutual learning. In the case of sustainable housing solutions, a group discussion process, in which facts are listed by participants (who remain anonymous) without taking into account local social structures, can lead to conclusions that are not accepted by the community. Hence, this paper explains how a Delphi Survey can be designed as a qualitative element of participatory action research. Therefore, the WohL Study and its qualitative Delphi Survey are presented, followed by a methodological reflection on the findings. It becomes clear that consensus and anonymity have to be balanced with solution sustainability. Criteria like the selection of participants, the process of group discussion as well as data collection and analysis have to be adapted to the specific field to be explored. New, diversity-sensitive and method-based approaches to decision making pave the way for a transformation of housing that must imply “vacancies” are to be (re)used, but also that collective decision-making brings “overlooked” groups “back into play.” Ultimately, the essential prerequisite for managing the transformation is the participation of the people of the community.

Relevance of deep sequence models for recognising automated construction activities: a case study on a low-rise construction system

Recognising activities of construction equipment is essential for monitoring productivity, construction progress, safety, and environmental impacts. While there have been many studies on activity recognition of earth excavation and moving equipment, activity identification of Automated Construction Systems (ACS) has been rarely attempted. Especially for low-rise ACS that offers energy-efficient, cost-effective solutions for urgent housing needs, and provides more affordable living options for a broader population. Deep learning methods have gained a lot of attention because of their ability to perform classification without manually extracting relevant features. This study evaluates the feasibility of deep sequence models for developing an activity recognition framework for low-rise automated construction equipment. Time series acceleration data was collected from the structure to identify major operation classes of an ACS. Long Short Term Memory Networks (LSTM) were applied for identifying the activity classes and the performance was compared with that of traditional machine learning classifiers. Diverse augmentation methods were adopted for generating datasets for training the deep learning classifiers. Several recently published literature seem to establish the superiority of complex deep learning techniques over traditional machine learning algorithms regardless of the application context. However, the results of this study show that all the conventional machine learning classifiers perform equivalently or better than deep learning classifiers in identifying activities of the ACS. The performance of the deep learning classifiers is affected by the lack of diversity in the initial dataset. If the augmented dataset significantly alters the characteristics of the original dataset, it may not deliver good recognition results.