Month: April 2019

Efficient, environmentally-friendly and exceedingly cost-effective, smart lighting has emerged as a crucial component for smart buildings and cities alike. Smart light bulbs and smart light sockets have abilities that go far beyond merely responding to lighting needs. They can also create a layer of sensors across an entire facility that will let collect data and ultimately drive better experiences for the building’s occupants. The traditional large office buildings in which light switches are “hidden” are probably a thing of the past. The current trend to individually controlled lights, with the ability for each individual user to select their preferred lighting levels, is potentially a significant power saver and the use of more modern lighting technologies also reduces the amount of heat generated by more efficient luminaires.

Energy efficiency and big savings

A combination of lower costs of entry and increased savings makes implementing a smart building as tempting as ever.

Commercial buildings could save up to $60 billion between 2014 and 2030 with a “comprehensive building labeling and benchmarking program. Intelligent efficiency measures applied to just 35% of eligible commercial floor area in buildings with 50,000 or more square feet could save upwards of 50 TWh by 2030, assuming a conservative savings estimate of 20% – more than 1% of U.S. projected energy use by that year.

Lighting controls have come a long way in the past decade, producing a range of solutions. The biggest drivers in development are energy codes, falling cost, miniaturization of sensors and network integration hardware, advances in wireless technology, and rapidly growing demand for highly controllable LED lighting. Here is a list of the top eight most important types of lighting controls.

1. Traditional controls — Traditional lighting controls include standalone devices (e.g., switches) for control of local loads and centralized panels for control of large loads.

2. Luminaire- and room-based control systems — based systems embed or integrate sensors within luminaires, enabling them to respond individually for greater flexibility and energy savings. Room-based control systems package lighting controllers and input devices for autonomous, plug-and-play, preprogrammed room lighting control. In both cases, the lighting controllers may be networked, which allows programming.

3. Building- and enterprise-based control systems — In this system, lighting controllers are networked across a building or multiple buildings. Facility managers can then program all lighting control using operating software and potentially pull performance and other data to a central server or the cloud.

The most suitable choice depends on the application and the operator’s skill level. What is particularly interesting for facility managers is that the need for a premium dimming ballast no longer limits dimming used to increase energy savings in occupied spaces. LED lighting is highly controllable, and the majority of LED luminaires feature dimming standard or as a standard option. Introducing more-advanced lighting control options in existing buildings is similarly also no longer limited by running low-voltage wiring between devices, as wireless connectivity eliminates that need.

Trends shaping the future of control.

Embedded controls —  The lighting industry is increasingly offering luminaires packaged with embedded sensors and, in some cases, lighting controllers. This simplifies installation while increasing flexibility of control response.

Wireless control — Many manufacturers offer lighting and control solutions that enable control points to communicate wirelessly, such as using radio waves. This eliminates the need for dedicated low-voltage wiring, a major benefit for controls installation in existing buildings. This potentially reduces the installed cost of lighting controls in existing buildings while making the upgrade simpler and less disruptive. In some solutions, the control points may be networked within a programmable, scalable system that generates useful data.

 Networked control —  An increasing number of lighting control solutions network all control points, assigning them unique addresses for individual or group programming. The solution may operate autonomously or integrate with other building systems. This approach offers numerous advantages, including detailed control zoning, distributed intelligence, zoning using software, programmability, data generation, and more. Coupled with wireless communication, it can be suitable in many lighting upgrade projects.

Energy efficiency organizations and utilities are now looking to get behind networked lighting controls in a big way. Estimating that one-third of all LED-based energy savings may be derived from connected lighting and controls by 2035, the Department of Energy is promoting the technology and working with industry to enhance it. The DesignLights Consortium recently developed a specification and Qualified Products List for networked lighting controls, which utilities are now using to develop rebate programs promoting the technology.

Data generation — Some lighting control systems allow data collection from control points connected via a digital wired or wireless network. The system may directly measure or estimate energy consumption or monitor operating parameters. Additional sensors embedded in the luminaire may collect data such as occupancy and temperature. In some outdoor lighting control systems, other sensors may be added that collect data on everything from carbon monoxide to snowfall.

Data is fed to a server or to the cloud for retrieval and use via software. Energy consumption data may be analyzed and shared for a variety of purposes. Monitored conditions may prompt alarms for maintenance response.

Color tuning — With LEDs, it is relatively economical to provide users the ability to adjust lighting correlated color temperature (CCT), or shade of white light. With tunable-white LED lighting, users can adjust light source CCT with separately dimming arrays of warm- and cool-white LEDs. Other colors may be added to enhance the available color spectrum and ensure good color rendering. Two other approaches are dim-to-warm (LED products that dim to a very warm white similar to incandescent dimming) and full color tuning (separately dimmable red, green and blue LEDs plus amber or white and potentially other colors).

With the newest breakthroughs artificial intelligence (AI) has offered in the fields of robotics, self-driven cars, finance, and healthcare, energy companies are now exploring the possibilities of incorporating AI to increase the prospects of more efficient consumption of energy. Several artificial intelligence courses are already being developed to facilitate learning in the field of AI. The ability to compress and analyze large sets of data can help brands monitor and interpret the data produced by energy industries to optimize energy consumption.

Energy Storage:

The number was only predicted to double, but grew at a much faster pace than even the most optimistic experts expected. A renewable solution to the energy storage problem was much sought after. With the increase in storage capacity and technological emergence, AI has emerged to boost efficiency and sustainability. P

Accident Management:
Accidents and instrument failures are a common occurrence in the energy industry. Time and again, human errors and failure to thoroughly check equipment for safety and maintenance issues can lead to massive equipment failures and irreversible losses. Artificial intelligence is now being used to detect faults by observing pieces of equipment. Timely detection of these failures can thus not only save money and time, but it can also save lives.

AI solutions for areas in manufacturing, energy, oil and gas, amongst others are use a combination of analytics, sensors, and operational data to forecast any possible failures of critical infrastructure. SparkCognition was also granted an award in December 2017 by the Department of Energy for using artificial intelligence to enhancing coal-fired power plants.

Grid Management:
Modern power grids gather energy from multiple energy sources, including wind, solar, and coal. Operating and managing massive power grids systems has become more complicated. Artificial intelligence increases efficiency and stability to these energy sources through its ability by analzying large datasets in a short frame of time. This has led to the development of smart grids, which are designed to handle multiple energy sources at the same time efficiently.

Energy Consumption:
Excessive energy consumption is a global problem that is being faced by developed and emerging countries alike. To achieve a more sustainable consumption of energy, artificial intelligence is being used to monitor the energy consumption behavior of individuals and businesses. Many AI-based startups are now offering practical solutions to optimize this energy usage.

Energy Forecasting:
Renewable energy sources such as wind and solar power come with a constant challenge of unreliability. Though sustainable, these weather-dependent power sources often fluctuate in their energy, thus proving inefficient to power companies in the long run. Energy provider Xcel is using AI to solve these very challenges. Xcel uses National Center for Atmospheric Research’s new AI-based data mining method to access weather reports with precision and extensive detail. Xcel’s AI systems mine a combination of data from weather stations, local satellite reports, as well as wind farms. The algorithms driving these systems then identify patterns within the collected data sets to make relevant predictions.

The importance of developing and incorporating renewable sources of energy has been repeatedly stressed upon by government and environmentalists alike. Owing to the variable nature of renewable sources, suppliers earlier mostly relied on natural sources of energy. However, with the integration of artificial intelligence in renewable energy sources, an increase in energy efficiency does not seem far off.

The built environment affects our well-being and this, in turn, influences our effectiveness in the workplace. Poor environments contribute to absenteeism and to people not working as well as they might. This is an enormous cost to the nation. High-quality environmental design is an investment, as occupants are healthier, staff-retention rates are higher, productivity is higher and sustainability ideas are more likely to be met. Workplaces reflect the culture of
companies and are places that are not just functional and convenient but give the occupant a wholesome experience in terms of body and spirit.

Buildings Affect People’s Health
Over the past 20 years, it has been empirically assessed that most building environments have a direct effect on the occupants’ physical and psychological health, well-being and performance; however, it is only through more recent studies that a clearer understanding of the occupied environment has been discovered. There is a need to: create greater public awareness of the health impacts of buildings; increase the focus on better tools and methodologies to collect data and measure healthy, impacts; and encourage building codes to place increased emphasis on healthier
building practices. If we only concentrate on energy we are in danger of neglecting the real purpose of architecture which is to provide for people’s well-being. A balance between these requirements is necessary.

Intelligent sustainable buildings for smart sustainable cities

The concept of “intelligent buildings” has been around for a number of years and has relied on the ability of individual systems within the buildings to communicate, to integrate and to perform in a manner allowing for numerous, complex, controls to generate a much-enhanced response to many kinds of stimuli. Thus, the argument of intelligence can reasonably be associated with the ability of intelligent buildings to function in an enhanced manner yielding many benefits for the occupants, the operators, the owners and reducing the overall environment impact.

Benefits and opportunities which these intercommunications, or intelligence, can provide:

• Access control and security systems

The access control system should be integrated with the fire system, lighting system and the HVAC system. With these forms of integration, the system “intelligence” can allow a user to enter the building and the information that this user has presented in terms of his credentials will be signalled to a number of independent systems.

• Elevators and escalators

Through suitable programming, the number of elevators being used at any one time can be optimized to address schedules, loads and potentially, emergencies;e.g., if paramedics require an elevator, it can be automatically configured to provide exclusive use for such purposes under an emergency situation.

•  Lighting

The traditional large office buildings in which light switches are “hidden” are probably a thing of the past. The current trend to individually controlled lights, with the ability for each individual user to select their preferred lighting levels, is potentially a significant power saver and the use of more modern lighting technologies also reduces the amount of heat generated by more efficient luminaires.

•  Signage

There have been evident changes applicable to signage technology. Signage can readily be shown on screens, and include any required graphics thereby ensuring that language and situational variations are readily addressed. Thus standard signage can carry routine messages including hours of operation or the length of line-ups or delays.

• Building condition monitoring

Intelligent building technologies open the opportunity to facilitate the monitoring of a building’s condition. Transducers and sensors are available to measure most building related parameters and in any given situation, there may be particular needs driving their specific use. Under appropriate conditions some or all of the following may be appropriate and would then be communicated to a central monitoring facility.

Climate change adaptation

Climate Change related severe weather events are increasing in frequency and severity. These severe weather events include (but are not limited to):

• Urban floods;
• Extended heat waves;
• Ice storms;
• Extended cold spells;
• High winds / tornadoes / hurricanes.

These weather events have both a long term and short impact on the commercial building infrastructure in cities.

During short-term events, building infrastructure is impacted by major structural damage, damage to a building’s support and utility systems, closure and loss of revenue among other items.  In order to prevent damage from flooding events, major HVAC, electrical and communication equipment should not be located below or on grade locations or if it is not possible to move equipment above grade then equipment rooms should be sealed against water intrusion.

• Demand response capability means that the intelligent building is able to reduce the building’s electrical load for HVAC and/or lighting during periods of high system wide demand, typically at the request of, and perhaps with incentives from the utility. This is particularly needed during extended heat waves to ensure that power grids are not overly stressed.
• Proper design of external landscaping and storm water management facilities can reduce the potential effects of severe rainstorms and urban flooding.
• Intelligent buildings normally also have back up power systems that can automatically provide power for short or extended periods of time to allow for evacuation or maintain building operations.

Smart Cities yields many benefits for society, including enhanced opportunities for education, improved job prospects, better access to healthcare and cleaner water. Yet it is also associated with immense societal and environmental challenges. Inefficient planning and management practices lead to unsustainable settlements that do not enable people to advance personally, socially or economically. Smart and innovative technologies, including artificial intelligence, are revolutionising the way cities address the challenges associated with smart growth.

AI in Smart Cities

Such technologies help cities to utilise existing assets more effectively, allocate resources more efficiently and improve how data and information are managed and shared across systems. Increasingly, satellite data is becoming a fundamental component of smart cities and an essential tool for city management and governance. From understanding connectivity between cities to measuring economic growth, detecting power outages or identifying where resources should be allocated after disasters, the increasing availability of satellite data is transforming how cities are managed and helping to improve their functionality.

From the point of view of urban governance, machine learning and artificial intelligence (AI) provide near-real-time information on how cities change in practice, e.g. through the conversion of green spaces into built-up structures. By ‘teaching’ computers what to look for in satellite images, rapidly expanding sources of satellite data are leveraged in combination with machine learning algorithms to quickly reveal how actual city development aligns with planning and zoning or which communities are most prone to flooding. Machine learning techniques help to automatically detect and map different types of land cover and land use across space and time, and generate important insights, analytics and visualisations.

AI  a buzzword, a kind of magic formula

Today, AI is almost a buzzword, a kind of magic formula, based on some ‘intelligent agents’ and sophisticated algorithms that make decisions and take action for humans. But AI will never replace human validation or effective governance on the ground. ‘Smart’ technologies that collect data on the ground or from space must be leveraged to monitor and manage urban systems and to provide guidance and recommendations for better decision-making, which will in turn make cities more sustainable.

Planning for scalability and sustainability

Plan for both physical and digital scalability. If you want to upscale activities to other locations or cities by installing additional sensors or performing additional analytics – does the system allow for this?

Consider the longevity of the project and how the hardware may be used during and after it has completed. In some circumstances a Service Level Agreement (SLA) for maintenance or drift correction may be needed.

If you are building AI feedback into the system, it is good to make it as adaptive as possible. This allows systems to be able to take advantage of suggested optimisation by ensuring capacity to extend the functionality of the hardware and software, should it be identified as desirable by the AI.