Cues, Data, and Facility Management: Edge Analytics and Machine Learning Changing The Way We Work.

Today’s digital transformation is impacting every industry. Technology is disrupting the way organizations do business and the way we live our lives. The pace of innovation in facilities management is faster than before, fueled by a perfect storm of exponential technologies and the rising adoption of artificial intelligence (AI), machine learning (ML), and other new digital capabilities.

FM Operations in an increasingly digital world means that today’s facilities managers must adopt new tools and techniques to meet the challenges of tomorrow.?

In this industry, people are responsible for the upkeep, installation, and monitoring of building hardware and software systems, industrial machinery and equipment, or other physical assets. In this sense, facilities management is more than just conducting janitorial work; instead, it can involve managing the environment more broadly, including safety concerns like fire protection and security.

With the help of machine learning and edge analytics, FM professionals are managing large campuses and facilities with growing demands for proactive measures and the need for increased security and safety combined with the complexity of aging assets and hardware.

Data Ingestion: A path to value creation.

Machine Learning describes algorithms that can learn without being explicitly programmed, with exposure and experience to the set tasks, learns from data, makes more accurate predictions, and makes better strategic decisions about operations by extracting insights from the data. When it comes to facility management, machine learning addresses many different business issues. For example, it can optimize energy usage, predict maintenance needs, or optimize resource management.

Edge Analytics is an umbrella term for analytics occurring on or near the edge of networks. Often used interchangeably with “fog computing,” it leverages the same computational power available in edge devices to perform analytics such as predictive maintenance and anomaly detection. The data generated on sensors for facilities are placed throughout the building, including the HVAC systems, lighting systems, and safety sensors. Processing data at the source avoids sending large amounts of data over the internet, which can sometimes be challenging for organizations today.

Machine learning and edge analytics go hand in hand. Processing data with edge analytics requires the data to transform into a format suitable for machine learning algorithms. Once the data is in a format ideal for machine learning, it sends it to the cloud, where it is analyzed and generates insights sending them back to the system, which uses the data to adjust operations or execute actions.

Capitalizing on the power of intelligence.

The program collects the data from sensors in the field, analyzes and generates insights in almost real-time, and increases the speed and accuracy of data insights, which is crucial in FM. Edge analytics is a type of analytics conducted close to the data source that minimizes the amount of data sent to the data center processing in real-time. By collecting and analyzing data on edge, organizations can reduce the time it takes to get insights, reducing the overall operation cost and allowing organizations to respond to events much more quickly.

The building blocks of intelligent facilities management.?

Facilities management is a growing market with high demand for new technologies.?A property’s team members can’t monitor every aspect of building operations by themselves; the technology to track several parts of the building’s performance at once, such as environment temperature, lighting levels, and air quality indices, among others, creates more efficient work environments for operational excellence and rapid responsiveness.

Adaptive Intelligence:

A smart building is modern, connected, and intelligent, with many features such as interactive control systems, sensors, and other information technology. These features allow occupants to use natural light, control their environment and improve the comfort level throughout the building.

Connected sensor networks and computing embedded in physical objects linked through a wireless network collect data like sound, temperature, pressure, and light, which translates into digital information. The sensors that monitor temperature, humidity, and power consumption are placed in different locations around buildings to provide a better idea of energy wastage or not appropriately conserved.

Predictive Maintenance:?

Technology solutions like ML and Edge Analytics infuse accountability and transparency in each area of operations. It facilitates real-time analysis of all asset data, procedures, management of work orders, equipment history, and service reports. The algorithms analyze and predict failures or take proactive actions to ensure minimal service disruption and precisely manage the risks associated with equipment failure.?

In most cases, algorithms look for specific data patterns, which allow the algorithms to predict the data patterns and instantly collect insights, make decisions, and have fewer false positives. They are less likely to produce false positives, so organizations don’t have to spend time investigating false alarms and instead focus on the issues that matter.?

?Safety and Security:

Advanced security alarms, analysis of live CCTV footage, and monitoring system alerts offer higher responsiveness to the needs by providing better security and safety. With machine learning and edge analytics technologies, FM managers monitor accurate real-time data collected to provide more insight and address incidents such as intrusion attempts, vandalism, and fires.?

When researching these incidents in the past, most companies would collect logs from a server or access them through a database. However, with this new technology, they have access to real-time data and can make decisions based on the information rather than just relying on what is stored offline.

Drones for facility condition assessments:

Drones provide a cost-effective and time-efficient way to get accurate information without scaffolding, professional surveys, and inspectors. They have the potential to improve data quality, reduce labor costs, and provide a complete 3D overview of large structures.

With the advent of drones, facility condition assessments have become much more accessible. There are many different drones available for facility condition assessments. Aerial imaging drones are a great way to ensure the roof is in good shape. The drone takes roof images, identifies damage or problem areas, and sends the information back for assessment. Another drone technology scans the parameters inside the building to determine the aging building conditions.?

Advanced HVAC technology and Indoor Air Quality:

There are several different types of sensors for location and remote sensing in intelligent buildings. These include thermal cameras,?door locks,?occupancy, and window sensors. By installing a combination of these sensors, it is possible to build a detailed picture of building operations and identify opportunities for improvement.

HVAC systems are designed with an indoor air quality (IAQ) function to keep the air clean in the building. They can also be integrated with outside air ventilation systems and work to improve indoor environmental quality (air, noise & light). Advanced HVAC technology relies on sensors, integrated control loops, and other cutting-edge technologies.?

The IAQ measures how well we’re controlling airborne contaminants in a building. Many factors can affect it. Thousands of pollutants released into the air in our daily lives lead to health problems if not appropriately managed by ventilation or other means of removal from the breathing zone of occupants and staff members.

Sustainable Planning:

Extreme weather events’ increased frequency and strength place significant pressure on building management teams worldwide. Temperatures are rising, meeting logistical challenges in more stringent safety standards for campus buildings. An increase in penalties for non-completion of these stages is combined to cause accelerating anxiety amongst those tasked with updating configuration schedules and corresponding expenditure budgets. Facilities management executives need proactive steps to reduce climate change risks to their assets and operations.

Intelligent buildings rely on sensors to collect data about the environment and the people within them. Real-time data helps to improve the functioning of the building by adjusting the temperature and lighting according to the number of people present. One key area where both technologies apply is location and remote sensing. Although still in its early stages, FM technologies optimize energy use, schedule maintenance tasks, and even monitor air quality. The process interprets data more effectively, allowing a more accurate understanding of what is happening inside a building leading to improved decision-making and lowering the effects of carbon footprints.

In Conclusion?

Traditional analytical methods like data logging and visualizations rely on data that has already been collected and take time to produce accurate insights. In contrast, edge analytics and machine learning collect real-time data and provide instantaneous insights making organizations nimbler and more responsive with their data. Combining these two data analytics tools will help you optimize operational efficiency, optimize costs, and improve customer experience.

To learn more about our Integrated Facility Management Solutions, please write to us at?[email protected]?or visit us at www.denaliassets.co.in