RULEX   INTERNET OF THINGS  

                 

 

 

Learn MoreAsk For a Demo

THE COMBINATION OF THE INTERNET OF THINGS(IoT) AND ARTIFICIAL INTELLIGENCE(AI) PROMISES TREMENDOUS OPPORTUNITIES 

 

Make automated decisions in real time

Change device behavior without reprogramming

Self-diagnose faults and service needs

Make businesses more efficient, productive and profitable

COST: WAITING FOR COMMODITY

 GPUS FPGAS,AND AI CHIPS 

~

To address the latency and risks of cloud-based predictions, decision processing must be moved to the edge devices. But using the math-based predictive models produced by conventional machine learning algorithms to make autonomous decisions on edge devices requires a dramatic increase in the processing power of those devices. IoT edge computing is currently done by adding Graphics Processing Units (GPUs), Floating Point Gate Arrays (FPGAs), or any of a variety of new, so-called “AI Chips” with intelligence programmed into the silicon. 

Currently about 30 billion IoT devices in use around the world contain simple low-cost commodity CPUs and supporting components. Many of them must operate on low battery power, and economies of scale demand a low unit cost. So, using math-based predictive analytics models means upgrading billions of devices to the next generation of chips.

 SPEED AND SECURITY 

WAITING FOR 5G AND BLOCKCHAIN

Neural Nets and other conventional machine learning algorithms produce massive predictive mathematical models that cannot be used on small compute devices at the network edge. To make predictions, edge apps must send enormous volumes of data to cloud-based data centers for processing by powerful prediction compute servers and then wait for a decision in return. Current network speeds are insufficient for high-volume, real-time Industrial IoT applications that rely on cloud computing. While 5G promises a solution, it’s one most will have to wait for.

 

 Another issue is that sending sensor data and control decisions back and forth across the network exposes the applications to disruption and industrial espionage by cybercriminals – a particular issue for Industrial IoT platforms, when managing public utilities or complex IoT manufacturing and supply chain processes. And the hopelessly heterogeneous nature of the IoT hardware and software landscape makes it nearly impossible for any enterprise to thoroughly strengthen the security of their decision communications network to thwart such threats. Here again, blockchain promises a fix – someday.

 SPEED AND SECURITY 

WAITING FOR 5G AND BLOCKCHAIN

Neural Nets and other conventional machine learning algorithms produce massive predictive mathematical models that cannot be used on small compute devices at the network edge. To make predictions, edge apps must send enormous volumes of data to cloud-based data centers for processing by powerful prediction compute servers and then wait for a decision in return. Current network speeds are insufficient for high-volume, real-time Industrial IoT applications that rely on cloud computing. While 5G promises a solution, it’s one most will have to wait for.

 

 Another issue is that sending sensor data and control decisions back and forth across the network exposes the applications to disruption and industrial espionage by cybercriminals – a particular issue for Industrial IoT platforms, when managing public utilities or complex IoT manufacturing and supply chain processes. And the hopelessly heterogeneous nature of the IoT hardware and software landscape makes it nearly impossible for any enterprise to thoroughly strengthen the security of their decision communications network to thwart such threats. Here again, blockchain promises a fix – someday.

 SOLUTION 

 RULEX EDGE LOGIC NOW

p

 

Rulex AI is powered by unique proprietary machine learning algorithms that produce predictive models based on logic rather than math, enabling high performance autonomous edge intelligence on existing low-power commodity edge devices. Rulex’s if-then logical decision models are compact and efficient, allowing even complex predictions to be made on large data volumes on the smallest CPUs.

 SOLUTION 

RULEX EDGE LOGIC NOW

 

Rulex AI is powered by unique proprietary machine learning algorithms that produce predictive models based on logic rather than math, enabling high performance autonomous edge intelligence on existing low-power commodity edge devices. Rulex’s if-then logical decision models are compact and efficient, allowing even complex predictions to be made on large data volumes on the smallest CPUs.

RULEX  INDUSTRIAL IOT 

 

Industry 4.0, the “next Industrial Revolution,” is happening now. Across many industries, including manufacturing, agriculture, logistics, energy, public utilities, transportation, healthcare and others, enterprises are looking to IoT technologies to provide dramatic improvements in process and operational efficiency, cost savings, worker productivity, data security, and equipment reliability.

For the Industrial IoT, Rulex adds autonomous edge intelligence to a wide variety of existing devices, including embedded systems, programmable logic controllers, SCADA systems, and network gateways. Rulex offers applications and benefits including:

Predictive equipment maintenance – reduced downtime and increased productivity

Automated safety incident prediction – rapid, compliant response readiness

Real-time sensor signal prediction – optimized operations and right-size machine loads

Production defect prediction – real-time adjustment of machinery control parameters

Predictive energy management – optimized consumption and excessive use prevention

RULEX  MEDICAL IOT 

 

Healthcare providers of all sizes struggle now more than ever to lower operating costs and improve practitioner productivity while preserving the highest possible quality of care and regulatory compliance. To help meet this challenge, clinics and hospitals are adopting a new generation of smart devices, cloud services, and mobile apps that are changing the way healthcare is delivered, from the ambulance, to the ER, to the hospital room, to home patient care.

It is the Internet of Medical Things, and it is at the heart of digital transformation for healthcare providers around the world. The IoT in healthcare means medical devices of all kinds are being equipped with sensors, processors, and communications capabilities for faster data collection, deeper condition analysis, and more accurate and effective response and treatment.

But in mobile and home care medical applications, connectivity to the cloud introduces latency that can make the difference between life and death for the patient. In the hospital, the expense of enabling medical device intelligence with specialized prediction processors makes many of the most promising devices unaffordable.

And for medical device manufacturers and application providers, the regulatory certification of solutions employing embedded “black box” AI dramatically increases the time, cost, and risk of developing new products and bringing them to market. The reason: predictive decisions cannot be easily explained.

For medical IoT solution providers, Rulex’s explainable edge intelligence brings benefits to IoT applications in healthcare that no other type of AI can provide:

For the Industrial IoT, Rulex adds autonomous edge intelligence to a wide variety of existing devices, including embedded systems, programmable logic controllers, SCADA systems, and network gateways. Rulex offers applications and benefits including:

Real-time sensor data processing and event response

Accurate prediction of device failures and maintenance needs

Automated, explainable procedural guidance for practitioners

Increased efficiency in managing equipment and staff assignment

More effective and reliable mobile and home care medical IoT solutions

RULEX  MOBILE IOT 

 

The Mobile IoT promises self-driving cars and trucks in the near future. But it is here now in the form of warehouse picking robots, site inspection drones, vehicle telematics systems, and mobile apps for driver monitoring, traffic safety, route optimization, and many other applications.

But current Mobile IoT solutions cannot make predictions at the edge; they must send enormous amounts of data to the cloud and wait for the black box algorithm to work its magic and return a prediction to the edge. This is not a good solution when a warehouse worker stops to tie their shoe in the path of a brawny, silent, and not-so-bright electric mobile robot.

Today, developers of smarter and more innovative Mobile IoT solutions must wait at the drawing board for the mass adoption of 5G and mass production of AI chips. Or, they could just use Rulex now.

Rulex’s rule-based predictive models are compact and can be rapidly downloaded and continuously updated on nearly any mobile processor. They can process huge amounts of IoT sensor data to enable complex, real-time predictions with no need for cloud communications.

For Mobile IoT developers, providers, and integrators, Rulex’s logical edge intelligence enables next-gen solutions with these advantages over other AI technologies:

No-code, visual mobile decision developmen

High performance on low-power processors

No need for data science skills

Fast, efficient memory compression

RULEX  MOBILE IOT 

 

The Mobile IoT promises self-driving cars and trucks in the near future. But it is here now in the form of warehouse picking robots, site inspection drones, vehicle telematics systems, and mobile apps for driver monitoring, traffic safety, route optimization, and many other applications.

But current Mobile IoT solutions cannot make predictions at the edge; they must send enormous amounts of data to the cloud and wait for the black box algorithm to work its magic and return a prediction to the edge. This is not a good solution when a warehouse worker stops to tie their shoe in the path of a brawny, silent, and not-so-bright electric mobile robot.

Today, developers of smarter and more innovative Mobile IoT solutions must wait at the drawing board for the mass adoption of 5G and mass production of AI chips. Or, they could just use Rulex now.

Rulex’s rule-based predictive models are compact and can be rapidly downloaded and continuously updated on nearly any mobile processor. They can process huge amounts of IoT sensor data to enable complex, real-time predictions with no need for cloud communications.

For Mobile IoT developers, providers, and integrators, Rulex’s logical edge intelligence enables next-gen solutions with these advantages over other AI technologies:

No-code, visual mobile decision developmen

High performance on low-power processors

No need for data science skills

Fast, efficient memory compression

Email Us

For more information 

Privacy Policy [link]