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The Most Viewed B.Arch thesis projects in 2018

December 28, 2018

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On many counts, the year 2018 has been incredible for us at ALive!. First, we reached a new milestone of 350,000 views from nearly 200,000 visitors.

The Most Viewed B.Arch thesis projects in 2018 1

Second, in addition to architectural and interior design projects, we also published many op-eds, ideas, thesis projects and research. We started publishing Thesis projects last year and this year too we were overwhelmed with the number of requests to publish thesis projects from architecture students across India and even Bangladesh. B.Arch Thesis projects have been a great source of inspiration for many students and teachers. We thank everyone who submitted their projects for publication and also those who shared them on Social Media, to ensure that the information reaches the maximum people. If you wish to submit your thesis, or an architectural project, click on the link below.

Among all the B.Arch thesis projects published in 2018, we are happy to share the list of five most viewed thesis projects below.

5. Urban Food Hub, INA At New Delhi by Vipanchi Handa, SCHOOL OF PLANNING AND ARCHITECTURE, DELHI

The Thesis was guided by DR. AMIT HAJELA , AR. DEEPAK TANEJA

B.Arch Thesis: Urban Food Hub, INA At New Delhi by Vipanchi Handa, SCHOOL OF PLANNING AND ARCHITECTURE, DELHI

4. Revitilization of Le Corbusier’s Legacy: Sanskar Kendra, by Rahul Jadon, Faculty of Architecture, Dr. APJ AKTU, Lucknow

Guides: Prof. Mohd. Sabahat

3. Memorial for the rebels of land, at Pahartali, Chittagong – Md. Hansat, Bangladesh University

Guides and Advisors: Ar. Kazi Tarannum Hossain, Ar. Sefat Sultana, Ar. Mithun Chandra Nath., Ar. Iqbal Habib,, Ar. Bikash Saud Ansary, Ar. Qazi M. Arif, Ar. N R Khan

Memorial for the rebels of the land. Night view

2. JASHN-e-PUNJAB By Harkunwar Singh Kanwal, School of Planning and Architecture, Delhi

Thesis Guide: Ar. Manish Gulati and Ar. Sambuddha Sen

B.Arch Thesis: JASHAN-e-PUNJAB By Harkunwar Singh Kanwal, School of Planning and Architecture, Delhi

1. Centre for Art and Architecture: Role of an Urban Catalyst, New Delhi, by Mohammad Suhail

Guides: Ar. Ritu Gulati, Ar. Shikhar Singh

B.Arch Thesis - Center for Art & Architecture: Role of an urban catalyst - Mohammad Suhail

We congratulate everyone who shared their thesis projects with us, and hope they keep sharing more work in the future too. Wishing everyone an eventful and joyous 2019.

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Architecture Thesis Of The Year | ATY 2022

Published on July 06, 2022

ARCHITECTURE THESIS OF THE YEAR | ATY 2022

The most amazing Architecture Thesis of 2022!

After the overwhelming response from the first two editions, Charette is elated to announce the third edition of ‘Architecture Thesis of the Year Competition - ATY 2022’.

‘Architecture Thesis of the Year 2022’ is an international architecture thesis competition that aims to extend appreciation to the tireless effort and exceptional creativity of student theses in the field of Architecture. We seek to encourage young talent in bringing their path-breaking ideas to the forefront globally.

PREMISE Academic Design endeavours allow the free flow of unfettered ideas – experimental, bold, promising, and unconventional. An intensive architectural discourse and a collaborative design process are essential to developing ingenious solutions to complex problems of the future.

An Architecture Thesis is considered the avant-garde – pushing the boundaries of what is accepted as the norm in the architectural realm. It is the outcome of months of painstaking research and an excruciating design process yet it hardly gets any recognition beyond the design studio. It is imperative to share such revolutionary ideas with the entire fraternity to open up new possibilities for dialogue.

Competition Brief - https://thecharette.org/architecture-thesis-of-the-year/

AWARDS Exposure and recognition is the key to success for any designer. The ATY 2022 competition provides students with the opportunity to showcase their work on a global stage.

TROPHIES Custom Designed Trophies will be awarded & shipped to the Top 3 Winners.

CERTIFICATES Sharable and verifiable certificates of achievement will be awarded to the Winners, Honorable Mentions & Top 30.

INTERVIEW The Top 3 Winners will get an exclusive interview in both – written and video formats. Photos, interviews, and more information about the winners will be published on our website.

PUBLICATIONS The winning entries shall be published on Charette’s website & social media platforms and other international architecture websites partnered with us.

ELIGIBILITY ATY 2022 is open to architecture students of all nationalities and institutions. All Undergraduate/Bachelors and Graduate/Masters Thesis conducted in the calendar year 2017 – 2022 are eligible to participate. Group, as well as individual entries, are allowed.. The official language of the competition is English.

SUBMISSION GUIDELINES A total of 5 sheets of size 30 cm x 30 cm are to be submitted as a combined PDF document, which shall not exceed 5 MB.

Sheets 1 to 4: Graphic Representation Sheet 5: Text Summary

For more details visit - https://thecharette.org/architecture-thesis-of-the-year/

KEY DATES Advance Entry: 15 June - 15 July 2022 Early Entry: 16 July - 15 Aug 2022 Standard Entry: 16 Aug -15 Sep 2022 Last-Min Entry: 16 Sep -15 Oct 2022 Submission Deadline: 16 Oct 2022 Results: 15 Nov 2022

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2 Goel, Kanupriya
2 Jaiswal, Shweta
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Submitted by Pappal Suneja

Architectural thesis proposal: international cruise terminal at cochin, india, india architecture news - sep 10, 2018 - 21:33 42551 views.

This is Synopsis of Architectural Thesis Proposal submitted to McGAN'S Ooty School of Architecture by Felishia Susan , under the able guidance of architect- Pappal Suneja . On an Introductory note, the Government of India has recognized Cruise Tourism as a potential area to build the economy of the country. It has initiated a number of positive measures to promote the cruise industry in order to position India as a global cruising destination. As a part of its development initiatives, it has identified the 5 major Indian ports of Mumbai, Goa, Cochin, Mangalore, and Chennai to be developed as “world class’’ cruise terminals.

The Proposal - Live Project

In view of this, the Central Government of India has proposed to build a cruise terminal in the scenic port of Cochin (Willingdon Island). Cochin is one of the leading cruising destinations in the country. With its strategic location and proximity to the international waterways, it has the potential to become the most preferred cruising destination globally. The Port Trust of Cochin has thus begun planning a project to build and develop a new 6.7-hectare International Cruise Terminal and public plaza to meet the increasing volume of foreign visitors.

The Mission

This architectural thesis has been specially designed in view of the needs of the above proposal. The aim of the project is to comply with the design requirements of the government’s proposal and deliver an output that would befit the situation. The mission is to attract cruise traffic to the zone through architectural and structural analogies, incorporating climate responsive design strategies and the concept of energy efficient architecture to achieve the highest sustainability.

Design Outcome

This unique structure meets the design requirements of functionality, iconicity, accessibility, and sustainability as a single entity. It is a utopian, yet unassuming structure that coherently fits into its surroundings and skyline. The concept and organic design of plan and form are first of its kind in the cruise terminal industry, marking its distinctive character. The utopian design strategy will be a forerunner in the cruise terminal infrastructure development industry of the country in the years to come.

Concept

The architectural design of the structure responds to the functionality and its surroundings. Undulation is a functional concept derived from nature or rather present in nature in many hidden forms such as the rise and fall of sea waves. The formation of waves occurs in nature with the decrease in depth of water level, which is indicative of its relative closeness to the shore. Likely when a traveler, on a cruise, encounters a wave break it is indicative of having reached the shore. This instills in the travelers a sense of “home-coming” .

Hence, the concept of a wave break has been incorporated in form. The form of the building would thus create a sense of homecoming in the tourists and also display its functionality through its form. The wave can easily be associated with the sea and as a traveler on a cruise, approaching the shore, the pleasant sight of the structure would instantaneously reveal that it is a terminal facility. And as for the general public viewing it from ashore, it would create a sense of mysterious marvel and yet reveal that it is a cruise facility, through its abstractive form and its association to the sea.

All Images © Felishia Susan

> via McGAN'S Ooty School of Architecture

Master of Architecture in Project Management

Effective skills of Principal Management, Human Resources and Communication

A comprehensive two-year program spanning four semesters that holds affiliation with Mumbai University.

Aim The aim of a construction project management course is to equip students with the knowledge and skills necessary to plan, execute, and oversee construction projects efficiently. It covers project planning, scheduling, monitoring, contracts, budgeting, risk management, principal of management, human resource and communication, enabling individuals to successfully lead and complete construction projects within time and budget constraints.

Objective The objective of ‘construction project management’ course is to provide students with a foundational understanding of large-scale projects, sustainable project management principles, successful strategies, performance evaluation, effective stakeholder collaboration, and research skills development. This equips students to excel in managing complex construction projects while promoting sustainability and innovation.

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Congratulations to the achievers,

The results of B.Arch. course of University of Mumbai is declared recently and 4 students of IES’s College of Architecture are among top 10 ranks.

Prathamesh Patil is the University topper with agold medal. his CGPI is 9.81

Sujay Zende secured 3rd Rank with CGPI 9.70

Sayam Mulani Secured 4th Rank with CGPI 9.69 Sayam is also a top ranker of sem X with SGPI 10

Gargi Kulkarni secured 8th Rank with CGPI 9.51

Dholavira Interpretation & Research Centre | Design Development and Detailing

Information

Project Name: Dholavira Interpretation & Research Centre
Student Name: Prachi Nagar
Softwares/Plugins: AutoCAD , Rhinoceros 3d , Adobe Photoshop , V-Ray , Velux , Autodesk Flow Design
Discipline: Interior Design
Level: Bachelors Design Project
Institute: Faculty of Design - CEPT University
University: CEPT University
Location: Ahmedabad
Country: India

Excerpt: ‘Dholavira Interpretation & Research Centre’ – an academic project by Prachi Nagar from Faculty of Design, CEPT University, focuses on climate responsive building form. The project proposes an innovative architectural form, derived from passive design strategies, to maximize thermal comfort in the extreme climatic conditions of Dholavira, Kutch, India.

Introduction: The project focuses on designing an Interpretation and Research Centre at the famous Harappan archaeological site of Dholavira, located at Kutch, India. The design for the Centre was developed by keeping the extreme climatic conditions of Dholavira in mind. The primary criteria for design development were: uniform distribution of indirect Natural Light in the exhibition areas and passive design strategies to gain thermal comfort. The design was further developed using a set of secondary criteria, such as: zoning of various functions between public, semi-public and private areas, and articulation of the design with appropriate selection of materials/details, keeping the extreme climatic conditions of Dholavira in mind.

The functions of the Interpretation Centre were: Reception area, Interpretation / Exhibition Area, Cloak Room/ Lockers for visitors, welcoming Foyer, Documentation/ Photography room, Amphitheatre for screening of documentaries, Office for a curator, researchers and supporting staff, Toilets for Visitors and staffs, Cafeteria and Kitchen.

Site Context

Dholavira is the fifth largest archaeological excavated site of the Harappan civilization, which was discovered in the year 1968. It is located at Khadir Bet in Bhachau Taluka of Kutch District, in the state of Gujarat in western India. The Interpretation and Research Centre is placed on the arrival of the Dholavira site, marking as an entry point to the archaeological site and also providing necessary information about the site in the form of exhibition and orientation. The building further connects the visitors to the excavated archaeological site through a pedestrian bridge over an existing stream.

Dholavira archaeological site is located in the hot and arid region of Kutch district, with an extreme climate during the summer and winter seasons. During the summer, temperature ranges from 35 to 50 degree Celsius; and in the winter, temperature goes down in the range of 0 to 10 degree Celsius. The total annual rainfall in the region is 450 MM, making it a hot and arid landscape.

Design Process

The design process for developing the Centre began with creating a matrix of ideas with multiple solutions for desired criteria such as: design strategies for maximising views from the site, passive design strategies for heat and wind, design strategies for optimising natural light. Based on the matrix of ideas, the building form was developed, first by selecting and prioritising design ideas, and later by superimposing them to arrive at various iterations.

The design development took place along the following criteria:

To maximise the wind flow through the main spaces an aerodynamic form was explored that had a smaller opening (aperture) on the windward side and larger openings on the opposite side, creating a larger negative pressure (wind shadow); hence, maximising the wind flow through the space.
To prevent direct heat gain to the main spaces a skin, enclosing the main volumes, was explored
The exhibition space demands indirect light. The roof section, incorporating skylights, was explored to bring ways of bringing indirect light.
To get the right amount of lux levels in the exhibition space, simulations were done using VELUX software.

The final form was arrived for the Interpretation Center based on the analytical study and many iterations. In the second stage of the design process, an architectural language for the project was developed by applying appropriate material, resolving structure and various details.

Final Outcome

The final design for the Interpretation Centre has the following qualities/design features to achieve thermal comfort, desired lux level in the exhibition spaces, and views of the archaeological site from the proposed centre:

(Thermal Comfort) A double skin Structure to prevent direct heat exposure into the Centre act as a climatic barrier for the internal spaces.
(Thermal Comfort) An aerodynamic form that maximises wind flows through the main spaces
(Thermal Comfort) The openings in the main structure, on the windward side, work as air cooling agents with humidifiers to reduce the temperature of the wind flowing through the main spaces.
(Light) A roof with skylights that provides indirect light to all the main functioning spaces
(View) The openings in the skin are created to give perfect views of the excavated site, and generate curiosity amongst visitors to visit the excavated archaeological site.

The skin structure, wrapping the main spaces, was proposed with Glue laminated timber sections, interconnected with Mild Steel Pipes and braced with steel cables. The skin façade consists of Wooden planks and transparent glasses (to have a particular view of the excavated area). The main structure is made up of concrete with Aspen evaporative cooling pads for openings in a windward direction to maximize the natural cooling of the main spaces.

[This Academic Project has been published with text submitted by the student]

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The road toward AI: Fundamentals

There's no question that artificial intelligence (AI) is the talk of the town these days, overshadowing almost everything else in the world of technology. In this series of articles, we'll explore the road toward AI (Figure 1 ) and how your organization can smoothly transition toward incorporating AI into its platforms and applications.

Clean architecture isn't the only topic I cover, you know! So, welcome aboard as we steer our focus toward artificial intelligence and machine learning (for now, at least, as these principles will map on the domain of AI/ML as well).

Don't worry if AI is still a bit of a mystery to you—we'll start right from scratch. Think of this series of posts as an inverted pyramid, with each post building upon the last (Figure 2). We'll kick things off by laying down the basics and gradually move toward more advanced topics. As we progress, the discussion will branch out into various aspects of AI, providing you with a comprehensive understanding of its applications and implications. So, fasten your seatbelts and get ready to explore the exciting world of AI with me!

Is it AI, ML, or DL?

AI is a broad field that includes many different techniques—machine learning is just one of them.

Artificial intelligence

AI is about creating computer systems that can perform tasks that would normally require human intelligence. This could include things like understanding language, recognizing objects in images, or making decisions based on complex data.

For example, think about a virtual assistant like Siri or Alexa. These systems use AI to understand what you're saying, figure out what you want, and then provide you with the appropriate response.

AI is often perceived as a cutting-edge innovation, but that's not entirely accurate. My thesis, completed back in 2011, delved into topics that now resonate with machine learning concepts (see Figure 3). I focused on enabling drones to fly autonomously and designing algorithms to efficiently locate packages within warehouses based on probabilities of their positions. However, at that time, these functionalities were implemented using traditional methods like if-else statements and heuristic algorithms such as the traveling salesman and ant colony optimization.

Taking a step further back, around 2002, we encounter the beginning of iRobot Roomba, marking a significant milestone in autonomous vacuuming technology. Yet the roots of AI stretch back even further. In 1955, John McCarthy organized a workshop at Dartmouth on "artificial intelligence," marking the first usage of the term and laying the groundwork for its popularization over the years. Reflecting on these historical points illustrates the evolution of AI from its early stages to the sophisticated technologies we see today.

An online of the master paper, describing the process of letting a drone fly automatically.

Machine learning

Machine learning is like teaching a computer to learn from examples. Instead of giving the computer a set of rules to follow, you provide it with a bunch of data and let it figure out the patterns on its own. It's a bit like how you might learn to recognize different types of dogs by looking at pictures: you don't memorize a list of rules, but you start to recognize common features like floppy ears or wagging tails (i.e., pattern matching). Figure 4 shows an example of a person using their pattern-matching abilities to categorize objects.

For example, suppose you want to build a spam filter for your email. You could give the computer thousands of emails, some marked as spam and some as not spam. By analyzing the patterns in these emails, the computer can learn to recognize which ones are likely to be spam and which ones aren't (notice that manual labeling of the input/training data is a prerequisite for starting with machine learning).

Deep learning

Deep learning (DL) is a subset of machine learning that's inspired by the way the human brain works. It involves building neural networks, which are networks of interconnected nodes that are loosely modeled on the neurons in our brains (see Figure 5 for an artistic depiction of this). These networks are capable of learning increasingly complex representations of data by stacking layers of nodes on top of each other.

A classic example of deep learning in action is image recognition. By training a deep learning model on a large dataset of labeled images, the model can learn to recognize patterns like edges, shapes, and textures at different levels of abstraction. This allows it to accurately identify objects in new images, even ones it hasn't seen before. Figure 6 illustrates how in this process, a human being must first categorize the images in the dataset in order to then train the deep learning model on the appropriate information.

So, in summary, machine learning is about teaching computers to learn from data, AI is about creating systems that can perform tasks that would normally require human intelligence, and deep learning is a specific technique within machine learning that's inspired by the structure of the human brain.

Roadies and rock stars

In the context of discussing AI, we can draw a comparison to the dynamics of a concert. Imagine purchasing tickets to see your favorite band perform. More often than not, the focus lies in witnessing the rock stars take center stage, rather than appreciating the meticulous efforts of the roadies working behind the scenes. These unsung heroes are responsible for setting up the stage, orchestrating the lights and sound, and managing the PR and marketing efforts that make the concert possible. Figure 7 shows a few Red Hat "rock stars."

Similarly, within the landscape of AI/ML, a similar analogy can be drawn. The "rock stars" in this scenario are the models themselves, be it Gemini, GPT, LLaMa, Mistral, or others. These models capture our attention with their remarkable capabilities, such as generating text or recognizing images. However, their success is only made possible by the dedicated individuals working tirelessly behind the scenes.

These AI counterparts come in various roles: software developers, data scientists (sometimes regarded as rock stars themselves), platform engineers, product owners, and even the infrastructure. Much like the stage crew at a concert, they ensure the smooth operation of AI endeavors, from data collection and preprocessing to model training and deployment. Even the infrastructure quietly supports these AI models, though its significance may go unnoticed until a rare disruption, like a 502 error, brings it to our attention.

In essence, just as a rock concert thrives on collaboration between performers and the backstage crew, the success of AI and ML ventures relies on the collective efforts of both the models and the dedicated individuals who bring them to fruition.

Comparing AI/ML and gem mining

Before diving into the details of AI and ML processes, let's take a moment to draw parallels with the process of gem and gold mining. The gem mining process looks like this:

Miners venture into the waters to collect nuggets, hoping to find valuable gems or crystals among the regular rocks.
These nuggets are examined by gemologists or geologists who help identify the ones containing precious materials, filtering out the worthless rocks.
Then, the valuable materials are extracted from the nuggets, leaving behind pure substances ready for further processing .
Fourthly, craftsmen such as jewelers and goldsmiths transform these pure materials into sellable items like jewels or gold bars.

Finally, the finished products are sold—but the process doesn't end there. Just as with any product, there's a quality assurance phase where any defects are addressed and fixed by the craftsmens.

Now, you might wonder, what does this have to do with AI? In the next section, we'll uncover the intriguing connections between these processes.

AI/ML process

Although the title of this section refers to AI/ML processes, the focus of this section will primarily be on the ML process. We'll delve into other AI processes in the next section. For now, let's keep things high level. Don't worry—we'll dive deeper into each step in future articles.

To kick off, let's draw parallels with the gem mining process described earlier. The full process is depicted in Figure 8.

Surprisingly, ML processes share striking similarities, as shown in Figure 9.

Collecting nuggets from the water: Just as miners gather raw nuggets from the water, collecting data from APIs and applications initiates the ML process. However, not all data is relevant, requiring data engineers to filter and manipulate it.
Filtering out worthless rocks: Similar to separating valuable nuggets from worthless rocks, data analysts and/or data engineers sift through data to identify which pieces contribute to valuable insights and predictions for businesses.
Extraction of valuable materials: Extracting valuable materials from nuggets aligns with isolating valuable data in statistical databases. The importance of this step will be elaborated on in subsequent posts.
Crafting pure materials: Just as craftsmen transform materials into pure forms, data scientists design and train neural networks or (pre-trained) ML models based on datasets. They then refine or train these models with training data.
Selling jewels/gold bars: Deploying the ML model for consumption by applications mirrors the selling of jewels or gold bars. Additionally, quality assurance involves testing for, detecting, and rectifying model drift, which we'll explore further in later posts.

By drawing parallels with gem mining, we can unravel the complexity of the ML process, laying the groundwork for a deeper understanding in the posts to come.

Road toward AI

As earlier noted, future articles will focus on how you can transition from zero to fully embedded AI/ML, highlighting every step along the way. A more general view on the road toward AI will look like this:

Get your application platform mature.
Implement structured data and day 1 intelligence.
Introduce machine learning.

Step 1: Get your application platform mature

Data is the cornerstone of AI/ML initiatives, and the first step toward success lies in acquiring, refining, and managing your data effectively. This process begins with establishing a robust application platform , such as an event-driven architecture or microservices framework.

A solid application platform is crucial as it facilitates agile development and deployments. For instance, if a data engineer or analyst requires the integration of a new data field or API (e.g., a weather API), the platform should enable swift implementation within hours or days, not months.

Furthermore, the platform should support the replication of data in various formats and across different databases to cater to diverse analytical needs. We'll delve deeper into this aspect in subsequent posts.

By laying the groundwork with a solid application platform, organizations can ensure agility and responsiveness in managing and leveraging their data, setting the stage for successful AI/ML endeavors. See Figure 10 for an illustration of this process.

Step 2: Implement structured data and day 1 intelligence

Once your application platform is robust and agile, the next logical step is to implement a data platform. This platform serves as a structured data source for data engineers, data scientists, and business analysts. Beyond simply enabling structured data storage, it's crucial to consider implementing day-one intelligence capabilities. This intelligence acts as a shortcut toward developing ML models.

But what's the value in this approach? Well, traditionally, implementing machine learning requires vast amounts of data—terabytes or even petabytes—which may not be available from day one. However, leveraging tools like Spark and graph databases allows you to code basic intelligence into your platform using a limited dataset. This brings two significant benefits. Firstly, it provides intelligence from the very beginning, enhancing the platform's functionality and usefulness right from the start. Secondly, it helps validate the completeness of your dataset early on. Identifying missing data fields at an early stage allows you to address them promptly, preventing potential setbacks down the line.

This process introduces an AI flow into your platform. Even when incorporating ML in the future, this step remains relevant. While ML models operate as black boxes trained solely on patterns within the training data, the intelligence coded into the platform adds a layer of human logic to the predictions. This complementary approach (e.g., enabled with Kafka) ensures a more comprehensive and nuanced understanding of your data, ultimately enhancing the effectiveness of your AI and ML initiatives. Figure 11 depicts this step of the process.

Step 3: Introduce machine learning

Now that structured data is in place, your data analyst can begin exploring correlations, and/or data scientists can start implementing business requirements using ML models. At this stage, neural networks can be developed from scratch, or pre-trained models can serve as a baseline to speed up the design and training phases. However, it's essential to exercise caution when using pre-trained models, ensuring they align with data governance principles—more on this in future articles.

Once the model is designed and trained, it can be deployed, potentially alongside any shortcuts developed earlier, and seamlessly integrated into your applications or platform. However, the journey doesn't end here. Continuous testing and validation of the model's performance on new data are imperative. Detection of model drift, where the model's performance degrades over time due to changes in the data distribution, signals the need for retraining with the updated data.

Despite the allure of ML, adopting a MLOps approach requires consideration of CI/CD -like pipelines to streamline model development and deployment processes. We'll explore this further in forthcoming blog posts, diving deeper into the complexities of MLOps and its significance in maintaining model performance and reliability over time. Figure 12 illustrates a complete view of this entire process.

Now that we've outlined the basics of the AI/ML process, it's time to delve deeper and clear out the road toward AI. Stay tuned for updates as we progress further along this journey.

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LEED for Show: Exploring the Pitfalls of Building Green for Certification Alone

What is LEED

Sustainability has become a buzzword we can’t seem to get away from these days. And in the architecture community, that usually equates to whether a building is LEED-certified.

But what exactly does a LEED-certified building entail? LEED ((Leadership in Energy and Environmental Design) is the world’s most widely used green building rating system. (Anon., 2024) Its certification is supposed to provide a framework for healthy, highly effective, and economical green buildings, which offer environmental, social and governance benefits. The reality of these certified buildings however is a bit different.

Greenwashing

Although the concept of this certification is noble the follow-through has become a bit problematic. Many of these accreditations simply don’t reflect the entire picture of a building’s impact or usually fail to reflect what truly makes a building sustainable.

These certifications work on a point-based system. These points lead to several types of certifications –

LEED for Show Exploring the Pitfalls of Building Green for Certification Alone-Sheet1

This point system works on the philosophy of creating benchmarks rather than standards. This is done by creating a laundry list of green strategies to reach a green building design. This leads to many loopholes. By multiplying a few smaller strategies, LEED certification can be achieved even without important energy efficiencies. For example, minor elements like installing a bike rack get you a point, while adding a minimum number of parking spaces scores you too. When these smaller elements are added up it leads to higher points and a certification without any actual energy efficiency in the design. This enables Building Green for Certification Alone to achieve green glory in the simplest and least expensive way possible without contributing significantly to the environment.

Not only that but also the stage of acquiring these certifications is inefficient and unstable. Applicants need to acquire LEED status by presenting computer models that project the building will meet a certain threshold. They can also accomplish this before the structure is occupied. Buildings don’t need to demonstrate continued effectiveness. This leads to the entire system being easily fooled and leading to no real value.

Predictably, studies reveal that buildings with LEED certification typically have lower energy efficiency than those without certification. According to one study, several of the LEED-certified buildings were the least energy-efficient of all comparable buildings, including in Washington, D.C., home of the U.S. Green Building Council. (Roy, 2014)

LEED in India

An obvious example of the failure of LEED buildings can be found in the simple fact that India retained its third spot on the U.S. Green Building Council’s (USGBC) annual list of Top 10 Countries and Regions for LEED (Leadership in Energy and Environmental Design) in 2023. 248 projects, across both buildings and spaces, were certified for LEED in the country covering 7.2 million gross square metres (GSM) (Anon., 2024)

LEED for Show Exploring the Pitfalls of Building Green for Certification Alone-Sheet2

Anyone who has worked in the field in India can attest to how energy efficiency is very low in the list of priorities given in our building designs being executed. Our country’s climatic condition is a clear indication of the same.

Greenpower an initiative

There is a new initiative with an extra tariff for consumers where customers can opt for the Adani Electricity Green Tariff Initiative The switch can be done with an immediate billing cycle and customers will receive a green power certificate monthly with a separate green colour bill indicating a separate line item – Green Power Tariff. (Anon., 2021).

Consumers in urban areas pay a green tariff, which is used to generate renewable energy in non-urban areas and power households and commercial enterprises in those areas. In return, urban consumers get a certification of lower energy consumption on paper, without actually investing in energy-efficient designs.

Rise in Green Commerce

At the end of the day the 21 st century industries’ goals are all market-driven. A vast ecosystem of green commerce has grown in tandem with LEED, spurring sales in products ranging from solar panels to low-VOC paints and low-flow toilets. “ Green building is now a $1 trillion global industry,” Mahesh Ramanujam, the USGBC’s ex-CEO (Barth, 2018).

While the idea behind green buildings is noble and necessary, especially in today’s climatic conditions, this use of certifications has led to it being a much more paper-driven campaign to use the ideas encouraged by green building certifications as nothing more than a marketing tactic, without investing in all it encompasses.

A large part of their issue is that a well-designed building is often not translated to its construction and operation. The need of the hour is to look at building designs holistically. Green certification industries such as LEED need to focus on all parts – concept, execution and maintenance. Operations and maintenance play a large role in the efficiency of a given building. Even small tweaks to the HVAC or lighting can make as much difference as a more expensive physical upgrade.

References:

Anon., 2021. Adani Electricity launches Green Tariff Initiative to switch to renewable energy. [Online] Available at: https://www.livemint.com/companies/news/adani-electricity-launches-green-tariff-initiative-to-switch-to-renewable-energy-11622825876298.html [Accessed May 2024].

Anon., 2024. India ranks third globally LEED green building certification 2023. [Online] Available at: https://www.gbci.org/india-ranks-third-globally-leed-green-building-certification-2023 [Accessed Monday May 2024].

Barth, B., 2018. Is LEED Tough Enough for the Climate-Change Era?. [Online] Available at: https://www.bloomberg.com/news/articles/2018-06-05/reconsidering-leed-buildings-in-the-era-of-climate-change [Accessed May 2024].

Roy, A., 2014. Forbes. [Online] Available at: https://www.forbes.com/sites/realspin/2014/04/30/leed-certified-buildings-are-often-less-energy-efficient-than-uncertified-ones/?sh=31861df42554 [Accessed May 2024].

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Need an architectural visualization and illustration person for my
To make appropriate architectural drawings and illustrations and 3d. ... Need an architectural visualization and illustration person for my thesis project Anyone. Client active 7 hours ago ... India (12:31 am) Posted ...
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