Next Industrial Revolution Technologies (NirT) is a re-branding of a technology company founded in 2006, formerly known as Bytecode Consulting.
NirT focuses on bringing technologies that are meant to be for the future to your business now. By partnering with us, you ensure that your business is always a step ahead of your competition. Find our more by exploring our offerings here:
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The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
The definition of the Internet of things has evolved due to the convergence of multiple technologies, real-time analytics, machine learning, commodity sensors, and embedded systems. Traditional fields of embedded systems, wireless sensor networks, control systems, automation (including home and building automation), and others all contribute to enabling the Internet of Things. In the consumer market, IoT technology is most synonymous with products pertaining to the concept of the “smart home”, covering devices and appliances (such as lighting fixtures, thermostats, home security systems and cameras, and other home appliances) that support one or more common ecosystems, and can be controlled via devices associated with that ecosystem, such as smartphones and smart speakers.
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In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. Leading AI textbooks define the field as the study of “intelligent agents”: any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term “artificial intelligence” is often used to describe machines (or computers) that mimic “cognitive” functions that humans associate with the human mind, such as “learning” and “problem solving”.
As machines become increasingly capable, tasks considered to require “intelligence” are often removed from the definition of AI, a phenomenon known as the AI effect. A quip in Tesler’s Theorem says “AI is whatever hasn’t been done yet.” For instance, optical character recognition is frequently excluded from things considered to be AI, having become a routine technology. Modern machine capabilities generally classified as AI include successfully understanding human speech, competing at the highest level in strategic game systems (such as chess and Go), autonomously operating cars, intelligent routing in content delivery networks, and military simulations.
Artificial intelligence can be classified into three different types of systems:
Humanized artificial intelligence
NirT has the capabilities to transform your organiztion to fully realize the benefits of AI. Contact us today to begin your journey.
Virtual reality (VR) is a simulated experience that can be similar to or completely different from the real world. Applications of virtual reality can include entertainment (i.e. gaming) and educational purposes (i.e. medical or military training). Other, distinct types of VR style technology include augmented reality and mixed reality.
Currently standard virtual reality systems use either virtual reality headsets or multi-projected environments to generate realistic images, sounds and other sensations that simulate a user’s physical presence in a virtual environment. A person using virtual reality equipment is able to look around the artificial world, move around in it, and interact with virtual features or items. The effect is commonly created by VR headsets consisting of a head-mounted display with a small screen in front of the eyes, but can also be created through specially designed rooms with multiple large screens. Virtual reality typically incorporates auditory and video feedback, but may also allow other types of sensory and force feedback through haptic technology.
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Augmented reality (AR) is an interactive experience of a real-world environment where the objects that reside in the real world are enhanced by computer-generated perceptual information, sometimes across multiple sensory modalities, including visual, auditory, haptic, somatosensory and olfactory. AR can be defined as a system that fulfills three basic features: a combination of real and virtual worlds, real-time interaction, and accurate 3D registration of virtual and real objects. The overlaid sensory information can be constructive (i.e. additive to the natural environment), or destructive (i.e. masking of the natural environment). This experience is seamlessly interwoven with the physical world such that it is perceived as an immersive aspect of the real environment. In this way, augmented reality alters one’s ongoing perception of a real-world environment, whereas virtual reality completely replaces the user’s real-world environment with a simulated one. Augmented reality is related to two largely synonymous terms: mixed reality and computer-mediated reality.
The primary value of augmented reality is the manner in which components of the digital world blend into a person’s perception of the real world, not as a simple display of data, but through the integration of immersive sensations, which are perceived as natural parts of an environment.
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“Big data” is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. When we handle big data, we may not sample but simply observe and track what happens. Therefore, big data often includes data with sizes that exceed the capacity of traditional usual software to process within an acceptable time and value.
Current usage of the term big data tends to refer to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set.
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Robotic process automation (or RPA) is an emerging form of business process automation technology based on the notion of metaphorical software robots (bots) or artificial intelligence (AI) workers.
In traditional workflow automation tools, a software developer produces a list of actions to automate a task and interface to the back-end system using internal application programming interfaces (APIs) or dedicated scripting language. In contrast, RPA systems develop the action list by watching the user perform that task in the application’s graphical user interface (GUI), and then perform the automation by repeating those tasks directly in the GUI. This can lower the barrier to use of automation in products that might not otherwise feature APIs for this purpose.
RPA tools have strong technical similarities to graphical user interface testing tools. These tools also automate interactions with the GUI, and often do so by repeating a set of demonstration actions performed by a user. RPA tools differ from such systems including features that allow data to be handled in and between multiple applications, for instance, receiving email containing an invoice, extracting the data, and then typing that into a bookkeeping system.
The 3D printing process builds a three-dimensional object from a computer-aided design (CAD) model, usually by successively adding material layer by layer, which is why it is also called additive manufacturing, unlike conventional machining, casting and forging processes, where material is removed from a stock item (subtractive manufacturing) or poured into a mold and shaped by means of dies, presses and hammers.
The term “3D printing” covers a variety of processes in which material is joined or solidified under computer control to create a three-dimensional object, with material being added together (such as liquid molecules or powder grains being fused together), typically layer by layer.
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Perimeter Security and Access Control systems protect the external perimeter of a facility, control access to restricted areas, and detect and monitor anomalies. Access control includes the control of persons, vehicles, and materials through entrances and exists in a controlled area or premises. Perimeter detection, in contrast, is the detection of access to the outer limits of a detection area by means of physical barriers, sensors on physical barriers, or exterior sensors. Finally, intrusion alarm systems signal entry or attempted entry of a person or an object into the area or volume protected by the system.
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Advanced Metering Infrastructure (AMI) is an integrated network of sensors, smart meters, and software that empower end users to monitor and control utilities such as water, gas, and electricity. AMI systems enable the measurement and visualization of time-specific data in real-time which, combined with remote control capabilities, can help companies and households reduce overhead costs.
The application of AMI must be complemented by the utilization of advanced security systems to ensure that data and control capabilities cannot be tampered with. This is important because both direct billing and operational decisions are often determined by the data provides by an AMI system.
AMI is also commonly known as Advanced Metering Reading (AMR).
Autonomous robots are intelligent machines capable of performing tasks in the world independently of either direct human control or fixed programming. Examples range from autonomous drones, to industrial production robots, to your robotic vacuum cleaner. They combine expertise from the fields of artificial intelligence, robotics, and information science.
The autonomous robot must have the ability to perceive its environment, analyze situational data in order to make decisions based on what it perceives, and then modify its actions based on these decisions. For example, the scope of autonomy could include starting, stopping, maneuvering around obstacles, communicating to obstacles, and using appendages to manipulate obstacles.
There are few autonomous robots in operation today. Even most sophisticated, dynamic robots such as those used in an automotive factory perform according to static programming. And most “autonomous robots” are only semi-autonomous and will likely remain so even as more fundamental autonomy becomes technically feasible. For example, the Roomba vacuum cleaner does not move according to a pre-programmed route and can modify its route dynamically as its environment changes. However, it has a very limited degree of freedom that is determined by its programming.
The aim of predictive maintenance (PdM) is first to predict when equipment failure might occur, and secondly, to prevent the occurrence of the failure by performing maintenance. Monitoring for future failure allows maintenance to be planned before the failure occurs. Ideally, predictive maintenance allows the maintenance frequency to be as low as possible to prevent unplanned reactive maintenance, without incurring costs associated with doing too much preventive maintenance.
Predictive maintenance uses condition-monitoring equipment to evaluate an asset’s performance in real-time. A key element in this process is the Internet of Things (IoT). IoT allows for different assets and systems to connect, work together, and share, analyze and action data.
Building Energy Management Systems (BEMS) are computer-based systems that help to manage, control and monitor building technical services (HVAC, lighting etc.) and the energy consumption of devices used by the building. They provide the information and the tools that building managers need both to understand the energy usage of their buildings and to control and improve their buildings’ energy performance.
HVAC (heating, ventilating, and air conditioning) is the technology of indoor environmental control. Its goal is to manage air temperature, humidity, and quality to meet the needs of both people and industrial processes. With low-cost sensors, wireless connectivity and more powerful data processors, HVAC companies are now able to collect real-time performance data and monitor the condition of their equipment. Remote monitoring solutions can monitor hard to reach areas and sites in order to alert staff to breakage and heat or water damage in a cable. IoT can help the HVAC industry improve overall equipment effectiveness and save money by minimizing equipment failure and optimizing energy usage and performance levels.
A digital twin works as a bridge to connect the physical and the virtual world for a process, product or service. It is a digital replica of a living or non-living physical entity. With the development of IoT, a digital twin can constantly accumulate data and mutually transfer the information with the physical body during the life cycle of the system.
The object of the digital twin is to analyze data and monitor systems in order to head off problems before they occur, prevent downtime, develop new opportunities and even plan for the future.
Fleet management is an administrative approach that allows companies to organize and coordinate work vehicles with the aim to improve efficiency, reduce costs, and provide compliance with government regulations. While most commonly used for vehicle tracking, fleet management includes following and recording mechanical diagnostics and driver behavior.
Automated Fleet Management solutions to connect vehicles and monitor driver activities, allowing managers to gain an unprecedented level of insight into fleet performance and driver behavior. This enables them to know where vehicles and drivers are at all times, identify potential problems much sooner and mitigate risks before they become larger issues that can jeopardize client satisfaction, impact driver safety or increase costs.
The goal of a Smart city is to improve the fundamental infrastructure by providing a decent quality of life, a clean and sustainable environment through the application of intelligent solutions. Smart cities can be used in eight sectors: Mobility, Security, Healthcare, Energy, Water, Waste, Economic Development, Engagement, and community.
The Smart City Operations is an integrated system that enables the communication within the team and cross functions to optimize the efficiency of city operations and services. With real-time and transparent information, city officials are able to monitor what is happening in the city and how the city is evolving.