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We want to become a trusted brand in AI-based smart street lighting: Lord’s Mark Industries

Street lighting in India has come a long way from sodium vapour lamps to LEDs, thereby improving energy efficiency. The next paradigm is Artificial Intelligence (AI)-based street lighting that promises to take energy efficiency as well as data analytics to the next level. We have Sachidanand Upadhyay, Founder, Lord’s Mark Industries Pvt Ltd giving keen insights on the AI-based street lighting industry, whilst sharing his company’s ambition of becoming a trusted player in this niche space. An interview by Venugopal Pillai.

Let us start by understanding the role of Lord’s Mark Industries in the entire value chain in the AI-based street lighting business.

Lord’s Mark Industries is a company focused on advancing R&D strategies for the development of AI-powered solar street lighting. Lord’s has been one of the early entrants in the country’s solar street lighting segment and has successfully installed more than 1 lakh solar street lights on a pan-India basis. As we continue building on our technical competencies and synergize our operational efficiencies, we remain committed to offering pioneering solutions in solar street lighting and collaborating with the government and other stakeholders in expanding electricity access to a large section of the population.

 

We understand that Lord’s had an agreement with “Philips” brand for lighting equipment. Does this agreement cover street lights as well? As far as the AI software is concerned, do you have technology partners?

Lord’s Mark has entered into an agreement with Philips as channel partner for solar based lighting products. In 2018, we expanded the scope of our agreement as channel partner for government projects.  Lord’s has a close association with Philips and have been extensively promoting their energy-efficient products to the government. We have an in-house team for designing AI software for the development of cutting-edge solar lighting solutions. We initially learnt the smart applications of AI from a technological partner based in Germany.

 

Please explain the various AI-based functionalities of the smart street lights.

AI-based functionalities facilitate the intelligent management of street lighting through real-time monitoring techniques. An AI-powered smart street lighting model offer dynamic illumination, dimming and brightening automatically as and when needed. Smart lighting systems help in increasing energy efficiency and reducing power cost. It also has the potential to act as a data capturing mode for various security agencies.

 

Assuming that smart street lights have features like remote switching, remote luminosity regulation, etc, where are such “control rooms” located?

Smart street lights are generally controlled from Central Monitoring Units which can be based in the wards of cities or state districts. Operations can be controlled and managed from a centralized office of the agency implementing the street lighting operations. A loop room comprising many wards or formed between a few districts can also control street lights. Such rooms are pivotal for controlling and monitoring the functional aspects of street lights. They can also lead to a better understanding of why specific lighting systems don’t work by knowing the exact nature of the problem.

 

Lord’s, as we understand, undertook a pilot smart street lighting project in Neral, Maharashtra. Please discuss the project, and explain how Lord’s build on this experience to further its presence in this space? Incidentally, did this project cover any area under the Matheran Forest Department?

It was not a smart street lighting project, per se. We undertook a pilot project for normal solar street lighting in 2014 in Neral village, Raigad district, Maharashtra, The project, which was successfully completed and monitored for five years, did not come under the purview of the Matheran Forest Department. This project marked the foray of Lord’s into the lighting industry and enabled our team to gain firsthand exposure to handling smart lighting systems. It was also an interesting learning experience which gave us the confidence to expand our operational presence into this domain.

 

So far, where has Lord’s made its footprint with respect to AI-based smart street lighting?

We have established a significant footprint in AI-based smart street lighting in Uttar Pradesh and a few private projects in Andhra Pradesh and Gujarat.

Street lighting, especially in rural areas, falls under the purview of government schemes like DDUGJY, IPDS, etc. Is Lord’s associated with such schemes?

Street lighting in rural areas does fall under the purview of government schemes like DDUGJY, IPDS, etc, as well as various initiatives of EESL. It is also promoted by various state government nodal agencies formed for the promotion of renewable energy.

 

Please discuss the efficiency and energy saving achieved by incorporating “smart” features in street lighting.

By incorporating “smart” features in street lighting, one can have accurate data of actual number of working systems in a specific area. One can have the actual illumination (lux) level, as well as data on the number of hours a street was illuminated.

Smart features in street lighting also monitor the time-wise movement of people during the night. With smart street lighting, energy is never wasted and one can leverage the benefits of cost optimization. By knowing the efficiency of each component under smart street lighting, good vendors can be identified and quality products can be sourced from them.

 

Is Lord’s involved with the Street Lighting National Programme (SLNP) of EESL?

Yes, we are involved with the Street Lighting National Programme of EESL.

 

How important as a component would smart street lighting be in the context of smart cities? Is Lord’s associated with any smart city project?

Smart street lighting is an important component in the context of making smart city projects successful. Lord’s has been associated to the supply of few components in smart city projects. However, we have never undertaken a smart city project in its entirety.

We have the capability, expertise and the confidence to undertake and execute such projects and we are eyeing a few of them in future.

 

In India, the progress on street lighting has largely been moving from conventional incandescent/sodium vapour lamps to LED lamps. Please discuss the scope and challenges in equipping street lights with smart features, in a typical urban setup.

Our country is expediting the shift from conventional incandescent/sodium vapour lamps to LED lamps. The Government of India has set up various agencies like district specific project offices to implement such projects for the seamless transition to smart lighting alternatives.

Challenges faced by these agencies arise in the form of identifying the right companies and project partners. Government tendering processes can lead to wrong and unqualified parties winning bids; this can adversely affect project quality and render the project financially and operationally unviable. The government needs to formulate stringent criteria whereby only qualified vendors will be allowed to participate in the tendering process.

Other than this, there are no major challenges in the development or implementation of smart lighting projects in rural areas.

 

Please discuss the growth plans of Lord’s in the field of AI-based smart street lighting. Where do you see the business, say 5-7 years ahead?

Lords would be fully developed company with robust service delivery capabilities in terms of technology, product development, supply and installation, AMC and parting technology.

We foresee the emergence of AI-driven power systems lighting in every Indian home in the next 5 to 7 years. Key components from power saving to distribution and security features would be AI-based.

We look forward to positioning ourselves as one-stop utility solution providers to the industry. Lord’s will cement its presence as a renowned and trusted brand in the AI-based smart street lighting industry in the next five years.

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