For some, the term "building automation" may seem like a relatively new concept. In reality, building automation, as a working discipline, has been around for 30 years. The early 90's saw the advent of decentralized computers to provide digital monitoring and control of various elements within a building's environment. By the turn of the century many buildings were equipped with computers/controllers that could connect to the internet. These advances provided facility managers with the means to achieve greater control over many building parameters (temperature, lighting, access, security, etc.).

PointGrab is an Israel based business that offers a platform which includes an image sensing a cloud and hardware unit management program called CogniPoint, which they say might help building maintenance managers reduce operational costs by using AI to automate as well as enhance facility management. PointGrab claims computer users can integrate the CogniPoint formula of theirs into current building automation systems. Furthermore the Cognipoint sensor is actually installed to certain rooms in the structure to monitor the amount of occupants. The sensor could be hooked up to the buildings' present local area network (LAN), Power over Ethernet (POE) or perhaps WiFi connections. The company claims each of the sensor products of theirs are able to cover up to forty eight square meters (or maybe 520 sq ft).

The Gulf Cooperation Council (GCC) is ushering a new manufacturing era based on a modern industrial society, as the region's only conference and exhibition dedicated to automation is launched in Dubai with the backing of global industry leaders. The announcement of SPS Automation Middle East 2018 on Feb. 22, arrives at a pivotal time in the GCC automation sector, and comes as regional countries such as the UAE and Saudi Arabia take a lead role in adopting new manufacturing technologies. According to reports, the UAE is looking to invest $75 billion in the manufacturing sector by 2025, leading to automation requirements for various industries such as packaging, construction, oil and gas, food and beverage, paints and coatings, Nano-sensors and healthcare. Saudi too has big economic diversification plans with automation at the core, as highlighted by its 2017 announcement to build NEOM, a $500 billion, 26,500sqm metropolis on the Red Sea where all services and processes will be 100 percent fully automated. A key regional challenge though has been creating sufficient automation awareness, with global manufacturers calling out for a dedicated industry platform and focal point centered on the latest trends and technologies across all areas of industrial or building automation.

In building automation, sensors such as motion detectors, photocells, temperature, and CO2 and smoke detectors are used primarily for energy savings and safety. Next-generation buildings, however, are intended to be significantly more intelligent, with the capability to analyze space utilization, monitor occupants' comfort, and generate business intelligence. To support such robust features, building-automation infrastructure requires considerably richer information that details what's happening across the building space. Since current sensing solutions are limited in their ability to address this need, a new generation of smart sensors (see figure below) is required to enhance the accuracy, reliability, flexibility, and granularity of the data they provide. Data Analytics at the Sensor Node In the new era of the Internet of Things (IoT), there arises the opportunity to introduce a new approach to building automation that decentralizes the architecture and pushes the analytics processing to the edge (the sensor unit) instead of the cloud or a central server.

PointGrab has announced a new white paper that explores the impact of deep learning-based smart sensor technology on building automation management. The white paper was developed to help building automation industry stakeholders, from device manufacturers to building managers, better understand the long-term benefits of deep learning-based technology. The paper, "Smarter Sensors: How Deep Learning is Transforming Building Automation," addresses the challenges and opportunities presented by Internet of Things (IoT) device proliferation and data collection and analytics throughout the smart building ecosystem. In this data-rich environment, sensors can be much smarter by sourcing and analyzing richer levels of data and enabling the execution of more sophisticated tasks that go beyond traditional energy consumption management.