Categories
Applied Innovation

Can Technology Redefine Construction? Exploring the Transformative Power of AI in the Industry

Categories
Applied Innovation

Can Technology Redefine Construction? Exploring the Transformative Power of AI in the Industry

The phrases “artificial intelligence” (AI) and “machine learning” conjure up thoughts of cold, impersonal processes devoid of human touch in the world of technology. A deeper examination reveals, however, that these cutting-edge notions may, in fact, breathe life into businesses, particularly the construction industry.

Recent worries regarding the possible negative effects of AI on the labour have been expressed, and a high number of workers fear AI will hurt rather than benefit the workforce. Despite these reservations, it is critical to recognise the substantial beneficial influence that AI may have, particularly in the construction sector, when used appropriately.

Bridging the Divide Between Humanity and Technology

AI and machine learning technologies have the potential to improve the daily lives of construction workers. Rather of eliminating humans from the equation, these technologies enable people to do their jobs more efficiently. With the introduction and improvements in construction-related AI solutions, there has been a rise in discussions about the possible advantages and concerns.

Recognising the legitimate worries about AI, the construction sector is undergoing a paradigm change. AI and machine learning are emerging as crucial actors in the effort to keep projects on schedule while adopting new technology. These innovations not only move the sector ahead, but they also improve results for workers, contracting businesses, and end users.

The Transformative Power of AI 

This voyage into the realm of AI reveals a wide range of breakthroughs, from improving design quality and assuring workplace safety to proactive risk management and project longevity. We dig into the revolutionary potential of AI in this investigation, giving light on its role in everyday automation and how it matches with the human-centric character of the construction industry.

Improving Design Quality: In one notable case, a prominent workspace supplier used machine learning to forecast the frequency of space utilisation, resulting in optimised meeting room designs. In addition, a partnership between design software experts and AI specialists resulted in the development of an AI-powered building design system, which especially improved the layout optimisation for timber flooring.

Making Construction Sites Safer: The use of AI-powered computer vision in the construction sector has revolutionised safety procedures. This system analyses accidents, detects possible safety concerns, and ensures that safety standards are followed. Furthermore, AI streamlines incident reporting via real-time data monitoring and natural language processing. This dual strategy supports in effective safety management, making construction crews safer on the job.

Assessing and Reducing Risk: Artificial intelligence plays a critical role in risk assessment and reduction on building sites. A construction-focused AI system, for example, is meant to prioritise possible concerns, allowing for proactive control of costs and schedule risks. AI algorithms in the construction industry can do more than just identify problems; they can also discover root causes, forecast safety events, and provide continuous monitoring of high-risk parts of building projects. This proactive risk management technique helps to simplify procedures and avert problems.

Increasing Project Lifespan: The use of AI and machine learning may dramatically increase the lifespan of building projects. These technologies simplify facility management by categorising data and evaluating real-time conditions. This comprehensive strategy guarantees that construction projects have a long and well-maintained life cycle.

Advancing AI in Construction

Large portions of organised and interconnected data are required for AI to be successful. AI might capture design requirements, integrate design and construction teams, and automate drawing generation in the future. While artificial intelligence (AI) continues to have an impact on the construction industry, it should be considered as a tool that enhances human abilities, creativity, and inventiveness rather than a substitute. Finally, the growth of AI in building opens up intriguing possibilities. Adopting AI correctly may unlock the full potential of human creativity and invention, ensuring that the construction sector evolves and thrives in the digital era.

Are you captivated by the boundless opportunities that contemporary technologies present? Can you envision a potential revolution in your business through inventive solutions? If so, we extend an invitation to embark on an expedition of discovery and metamorphosis!

Let’s engage in a transformative collaboration. Get in touch with us at open-innovator@quotients.com

Categories
Applied Innovation

Transforming Clinical Trials Through Data Analytics and Risk Management

Categories
Applied Innovation

Transforming Clinical Trials Through Data Analytics and Risk Management


Clinical trials are similar to scientific tests carried out to evaluate novel medications or therapies prior to their release to the general population. To assure the security and efficacy of novel medicines, these studies include intricate procedures, vast volumes of data, and meticulous monitoring. Enter a ground-breaking platform that simplifies clinical trials’ data analytics and risk management processes.

A Shift in the Clinical Trials Landscape

Consider yourself a scientist in charge of a medical investigation. You are in charge of keeping an eye on a lot of data points, ensuring sure the trial is going according to plan, and looking for any potential risks that can jeopardize its success. This is a difficult undertaking, but data analytics platforms may assist you in making it simpler.

Visualization and Centralization of Data

The platform acts as a central digital repository for information gathered from multiple parties engaged in the clinical study. This contains medical records, test findings, and reviews from patients. The software turns this data into user-friendly graphics like graphs, charts, and diagrams rather than displaying it in a raw, overwhelming format. Researchers may more easily identify trends, patterns, and outliers that could otherwise be hidden in statistics thanks to these graphics.

Finding and Evaluating Risks

Finding possible hazards that might affect a clinical trial’s development and validity is a crucial component of managing it. By methodically comparing the trial’s ongoing actions with its established guidelines, it shines in this area. The platform indicates any inconsistencies as possible threats if they appear. The severity and possible effect of these hazards are then classified and evaluated.

Making decisions in real time

Real-time insights are one of the platform’s most noteworthy characteristics. Access to current data and risk assessments allows researchers and trial administrators to quickly make defensible judgments. This proactive strategy minimizes delays, lowers the possibility of negative outcomes, and boosts the trial’s overall success.

Collaboration and Enhanced Workflow

Teams from both on-site workers and central monitoring teams participate in clinical studies. By serving as a bridge, the platform enables effective cooperation and communication across various teams. It provides a workflow that is easily adaptable to direct daily interactions and duties, ensuring that everyone is on the same page and adhering to the stated plan. For accountability and quality assurance reasons, the platform also keeps track of activities completed, establishing a verifiable history.

Conclusion

In essence, the platform completely transforms how clinical trials are organized, tracked, and assessed. It enables researchers and stakeholders to take informed decisions that result in safer and more effective clinical trials by combining data from many sources and turning it into usable insights. The trial process is made more efficient and productive by its real-time risk assessment and collaboration capabilities. Tools like this are crucial in ensuring that new medicines are thoroughly vetted and introduced to patients with the greatest levels of safety and efficacy as the healthcare sector develops.

Please write to us at open-innovator@quotients.com to know more about such innovative solutions and partnership opportunities,

Categories
Innovator's Vista

How AI is Transforming Supply Chain Management

Categories
Innovator's Vista

How AI is Transforming Supply Chain Management

Supply chain management is an essential part of most businesses and is crucial for company success and customer satisfaction. Supply chain refers to the entire system comprising of individuals, organisations, resources, activities and technology that play their role from the procuring of the raw materials to the final delivery of the product to service. 

Each stage of a supply chain is essentially a different industry by itself so it is a very complex chain. With this the factors like rising customer expectations for faster lead times, expanded products and services, and demand for tailored experiences are adding to its complexity. 

Supply chain management, or SCM is a diverse business process that involves overseeing the mentioned functions and factors from flow of a good or service, delivery, customer experience and also ensuring profitability. Building end-to-end visibility, collaboration, and optimisation across inventory, order, logistics, and transportation management are important for effective SCM.

Implementing AI in supply-chain management can improve operations and solve key issues like forecasting, risk management, costing, delivery logistics, customer service etc. AI can help create models for demand forecasting, that give fairly accurate estimates of future demand against current stock. 

By using historical data with real-time data across multiple layers of the supply chain, it can provide data visualisations and indicate supply chain issues causes and effects, reduce or eliminate bottleneck complications, and identify opportunities.

AI also allows business plans to be integrated across multiple companies and stages of production hence better understand consumer demand trends, predict unexpected events and transportation issues. Through transportation automation and warehouse automation AI can ensure quicker order processing, more efficient inventory management, and timely delivery. 

There are startups offering AI-enabled solutions that allows enterprises to have complete visibility over delivery drivers. Through features like auto-order allocation and route optimisation, the platforms efficiently manage drivers to reduce delivery costs, increase customer experiences. Such companies are operating in industries like Food and Beverage, E-commerce, Pharmaceutical, Healthcare etc.

Bert Labs, a Bangalore based startup, focuses on efficiency improvements in energy, production, supply chain planning & logistics, along with reduction in carbon footprint. Similarly, Edgeverve, an Infosys company, has come up with TradeEdge, an intelligent supply chain management platform that enables channel visibility, improve retail execution, reach new markets faster.

There are many startups working in this evolving space of AI based supply chain management. Open Innovator plans to cover these startups in the next few months where we would be discussing their unique offerings and how they are solving the key issues related to this sector.


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