Smart Lighting: Artificial Intelligence and Machine Learning Application for LED Lighting | ELE Times

Artificial intelligence

Artificial intelligence is the study of machines built by humans that makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Using this technology, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data. It is the endeavor to replicate or simulate human intelligence in machines. The most familiar examples are Face detection and recognition, Chatbots, Google Maps etc.

The way AI is capable of changing the industry can be imagined by taking note of a project funded by The European Union which has successfully combined advanced research in computer vision and modern technology to develop a lighting control paradigm in which each person in the office perceives the entire office as ‘all lit’, while lights, which are not visible, are switched off. The software estimates the light propagation in offices in real-time and computes how much of it is perceived by the people. Then smart lighting control adjusts the lighting autonomously based on the presence of people and on their position within the office.

The concept works particularly well in large open-plan offices, as farther-away luminaires may be dimmed without altering the comfort of employees and their sense of security. The four-year project is a collaboration between Osram, the University of Verona and the Italian Institute of Technology (IIT) in Genova. Its remit was to come up with a method of delivering ‘maximum comfort and sense of security while granting large savings in energy consumption’.

The participants estimate that technology using this AI lighting control could expect to see savings in energy consumptions of up to 65 per cent. IIT provided unique expertise in the 3D light estimation in large and complex office scenes, from color and depth images provided by a modern RGB-D camera while the University of Verona brought in expert knowledge and design skills for estimating the gaze of people and their future motion with deep neural network model.

Artificial Intelligence seems to be the mutual evolutionary force in every industry, which promises to switch things up altogether. While the whole commotion around the technology is quite exciting and optimistic, for the general public it’s still an obscure dimension.

Smart Lighting

As kids you grow up watching superheroes and the world of whims and fancies. You spend your childhood dreaming of things you could control by mere clapping or making a sound. Till a few decades ago you’d be told, the superhero premise is magical but not practical. Technology has come a long way since then. Now, you can control the lights, set timers and schedules, and change colors with your smartphone or your voice if you have a smart assistant in your home. Thus it is safe to say, Artificial Intelligence has been lighting’s mojo in the new world.

AI for designers

The longing for a controllable lighting is envisioned through Self-learning algorithms, i.e. continuous auto commissioning through machine learning making it possible to have round the clock monitoring.

Lighting can be designed without huge tolerances, like in fade times of the systems. Future AI solutions could also help to make lighting design faster and more successful. For example, if the users of commonly used Lighting design software would store their data to a cloud database, it could then already be used to provide improved recommendations at the beginning of the project.

AI for installers

Installing a lighting system takes time, which depends on the quality of planning, building structures, lighting application, knowledge and experience of personnel, and so on. In the future, advanced digital twins, building information models and augmented reality supported by AI could speed up installation and decrease errors. A significant amount of time in the building industry is wasted due to ineffective coordination, whereas the objective is to equip the right team of technicians with the correct tools and materials at the required place and time. Solving these issues might prove to be an optimum place of action for AI.

AI for commissioning & configuration

Luminaires communicate with each other about their current light stage and learn sequential patterns in the occupancy around them. They can predict the occupancy in their area using the information they get from other luminaires, thus illuminate the area even if the user is at the very edge of the lighting area. This reduces the amount of effort for commissioning and programming the lighting control, and in case there is any restructuring in the layout of the area, re-commissioning is not necessary since the lights will learn and adapt to the new patterns.

AI for end users

Supervised learning can learn the user preferences by recording their selections. It is also possible to collect data from multiple sources and offer automatic lighting that fits user needs and make lighting recommendations. This can be achieved without AI, if environment and needs are not changing, by making sure that selected solutions are providing illumination well above lighting norms. As the needs do often change, users of the space develop different requirements. One way to solve this is to have user interfaces that allow users to change conditions. It has been seen that people tolerate quite bad lighting before starting to control it. Hence, control should not be left just to the users.

AI for building owners and facility

Building owners who are not tenants themselves can be incentivized by improving the profitability of their buildings. It is already possible not only to see what the problem is and where it is, but also to predict the malfunction of a component in a system. This can be done by analyzing historical data and predicting future events. For example lighting remains turned on even if there are no occupants in the space. This leads to excessive energy consumption. By combining the data of multiple sensors, fade times can be tuned according to real needs

Cons of thinking machines

Human challenge

Artificial Intelligence is deeply rooted in mathematics and computer science. Recent developments related to computational and algorithmic efficiency have lowered the barriers to entry, but the overall research output is still constrained to a niche group of scientists.

Data challenge

The first and foremost requirement of building robust AI based solutions is the availability and quality of data. The decision to incorporate such products in an existing portfolio is usually taken based on an initial analysis of available data. However, the quality of analysis is closely linked to the interpretability of data. A Forrester Infographic indicates that Data Quality (DQ) is one of the topmost challenges to successful implementation of AI systems in enterprises. According to Forrester analyst Michele Goetz, businesses lack a clear “understanding of data needed for ML models,” and thus struggle with data preparation in most cases.

Privacy challenge

Security is a serious challenge for companies that implement AI, which is based on voluminous amounts of data. A considerable chunk of this data is highly sensitive—vulnerable to breaches and identity theft. Security researchers have agreed on a common conclusion when it comes to AI—if the creator of a model unintentionally unveils information about the inner-workings of an AI algorithm, it will introduce serious security risks. Hands down, organizations must recognize the fact that data security and privacy are critical matters in today’s world. As AI is more widely embraced, hackers will find bugs and loopholes to exploit. Organizations need to stay one step ahead.

AI companies in lighting building a smarter tomorrow

Signify: Signify Holding, Philips Lighting N.V., Netherlands, is an industry leader in the lighting market. The company’s market experience and brand name allow it to capitalize on the fundamental market dynamics in the lighting industry and deliver innovative solutions that create value and ensure its growth. The company has a huge advantage over its competitors in smart lighting market, due to its extensive product portfolio, with lighting systems compatible with various connecting technologies ranging from DALI, KNX, and BACnet to ZigBee and EnOcean. The company aims to further invest in connected lighting systems to win contracts related to the supply of connected lighting systems and other lighting control equipment. It also adopts the strategy of acquisition. For instance, in October 2019, Signify acquired Cooper Lighting Solutions from Eaton. This acquisition would strengthen its position in the North American lighting market.

Legrand: Legrand S.A., France, is a global specialist in electrical and digital building infrastructures. The company has a strong product portfolio pertaining to the smart lighting market. This enables the company to maintain its leading position in this market. Legrand focuses on growth strategies such as acquisitions, partnerships, and product launches. For instance, in May 2019, the company launched wireless DLM systems, which were designed for easy installation, which in turn save cost and time; and thereby, benefit engineers, electrical contractors, and facility managers needing reliable, code-compliant lighting controls. Moreover, in December 2018, the company acquired Kenall, a leading manufacturer of innovative, energy-efficient, and sustainable specification-grade lighting and control solutions.

Acuity Brands: Acuity Brands, Inc., US, has identified the demand for energy-efficient lighting technologies in the North American market and is aggressively positioning itself to meet this demand. The company offers a wide range of lighting products at multiple price points and for a variety of applications. It is further introducing new or improved versions of its successful products to satisfy the evolving needs of its customers. It has recently undertaken strategic acquisitions and entered into partnerships with other companies to acquire new technologies and further enhance its product offerings.

GE Lighting (GE + Current): The Energy Connections and Lighting segment includes the GE Lighting business, which is primarily focused on consumer lighting applications in the US and Canada, and Current, powered by GE, which is focused on providing energy efficiency and productivity solutions for commercial, industrial, and municipal customers. The Current business, powered by GE, delivers energy efficiency and productivity solutions for commercial and industrial customers. Current combines infrastructure technologies such as LED with new sensor-enabled data networks and Predix-based digital applications to help its customers reduce energy costs and gain business productivity insights.

Eaton Corporation (Cooper Lighting): Eaton Corporation offers smart lighting solutions including smart dimmers, sensor-based switches, bridges, and software platforms. The company delivers a range of innovative and reliable indoor and outdoor smart lighting solutions, as well as control products specifically designed to maximize performance, energy efficiency, and cost savings. Eaton’s lighting solutions cater to the commercial, industrial, retail, institutional, residential, utility, and other markets. The company has manufacturing facilities at 284 locations in 42 countries. In October 2019, Eaton agreed to sale its lighting business to Signify Holding.

Osram: Osram is continuously increasing its focus on the fast-growing market for smart lighting and LED components. By reorganizing its business segments and eliminating underperforming businesses, the company seeks to target business-to-business (B2B) markets where there is scope to earn higher profits. Osram focuses on transforming itself into a high-tech company to target smart visible and invisible lighting technologies for visualization, sensing, and treatment applications. With the acquisition of BAG electronics (a Trilux subsidiary) in March 2018, the company aims to strengthen its portfolio of Digital Systems (DS) business and expand its distribution channels in Germany and Asia.

Lavanya Singh, Vellore Institute of Technology, Chennai

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