Companies in nearly every sector—including transportation, manufacturing, agriculture, utilities, and many others—are looking for ways to leverage data from legacy assets. But many are unsure how to do so cost-effectively.
Two key challenges drive up costs. First is the effort required to extract data from existing equipment. In many cases, legacy systems use specialized protocols unsuitable for IoT applications.
Take the transportation industry as an example. Trucks, buses, and other vehicles offer a wealth of telemetric data such as engine oil pressure and battery charge level. But these parameters are carried over the specialized SAE J1939 bus, which was not designed for data sharing over an IP network. As a result, engineers must create hardware and software that can transform the data into an IoT-friendly form—an expensive proposition.
The second problem is the difficulty of transporting data for analysis. This challenge is particularly severe for remote or mobile applications, where network connectivity may be slow or intermittent. But even when ample bandwidth is available, the costs of transmitting data may be prohibitively high.
I recently spoke with Jeff Knapp, President and CEO of Smart Connect Technologies, Inc., about the ways organizations can lower these barriers to IoT adoption. According to Knapp, the key is using ready-made technology.
“We use off-the-shelf hardware and don't require programming or proprietary drivers,” Knapp said, “which together dramatically lowers the cost of adoption and implementation.” Knapp said this approach not only reduces the upfront investment, it lowers the total cost of ownership.
Another critical strategy is processing data at the edge when possible. “It mitigates storage issues,” said Knapp. “It mitigates bandwidth issues and processing time.”
Off-the-Shelf Solutions for Specialized Requirements
To illustrate these methodologies, we’ll look at how transportation and transit organizations are transforming their fleets—whether it rides on rails, roads, or over the waves—into IoT-enabled smart transportation.
Consider the SmartConnect Gateway solution, which can collect and analyze real-time vehicle data at the edge to drive decision-making, as well as send specific data sets to the cloud to gain deeper insight into fleet and vehicle intelligence.
Smart Connect’s gateways run on off-the-shelf Intel® processor-based machines that are easily acquired from multiple manufacturers—such as the Dell gateway shown in Figure 1—allowing the solution to offer low total cost of ownership. The system uses a Security-Enhanced Linux (SELinux) OS that comes pre-loaded with secure, open standard software.
SmartConnect offers a variety of pre-engineered drivers for sectors including manufacturing, transportation, and utilities. In the case of transportation, the gateway can access Diagnostic Trouble Codes (DTCs), including:
- Fuel level
- Engine speed
- Intake manifold pressure
- Exhaust gas pressure
- Coolant level
- Coolant temperature
- Battery voltage
The gateway can normalize and analyze this data at the edge, enabling the system to make operational changes from the edge in real time, while en route. The gateway can also be programmed to issue alerts in real time using text and/or email—per customer management directive—to designated recipients. Upon reviewing and assessing the alert, the recipient can then advise the driver in the vehicle as to how to proceed.
Adding Value in the Cloud
The gateway can also securely upload data to a cloud platform provider such as Amazon Web Services, SAP, or IBM to analyze data, increasing value and functionality.
By capturing, aggregating, and storing telemetric data from multiple sources in the cloud for further processing, a transit agency can create an asset management program that generates maintenance and repair tickets across the fleet. Such a program can generate positive ROI through:
- Cutting downtime
- Mitigating breakdowns
- Optimizing resources
- Increasing efficiency
- Lowering fuel consumption
- Reducing pollution
- Enhancing safety
In the transportation and transit sector, this capability can greatly enhance older rail stock, trucks, buses, trailers, ships, and containers. For example, freight organizations can use data to extend the life of legacy equipment and monitor the condition of cargo. Transit organizations can use data to analyze which stations or stops passengers board on and depart from as well as enhance vehicle performance.
Golden Gate Transit Gains Greater Insights
As proof of concept, Golden Gate Transit—operated by the Golden Gate Bridge, Highway and Transportation District in San Francisco, California—equipped buses with sensors and cameras to capture engine and other data. The data is sent through the SmartConnect Gateway to IBM’s Watson IoT Platform to perform predictive maintenance monitoring of buses and their various engine components.
Golden Gate Transit uses IBM Maximo as its asset management software. Maximo enables Golden Gate to manage the lifecycle and maintenance of its assets as well as track failures and run preventive maintenance operations. Maximo also provides Golden Gate with the ability to manage its accounting, fuel, inventory, purchasing, and other resources.
The SmartConnect solution also enables Golden Gate to reduce pollution. By combining video from bus-mounted cameras with GPS, DTC, weather, and air quality data, the agency can optimize bus routes. This reduces engine idling and, therefore, pollution.
Optimization efforts can even take place dynamically, such as when an accident or an event—whether it’s a baseball game ending early or a spontaneous protest blocking the streets—unexpectedly brings traffic to a halt. By using data to rethink traffic in both real time and over the passage of time, Golden Gate can provide its customers with better service and improve the health and livability of the community.
Bring New Value to Legacy Equipment
Easing the burden on how much data must be uploaded to the cloud can not only save a significant amount of money, it can improve operations. Whether it’s boosting productivity, enabling predictive maintenance programs, increasing equipment and operational efficiencies, improving services, or enhancing safety and security, edge processing unlocks new ways to leverage data from legacy equipment.
That’s why selecting the right comprehensive IoT solution that can perform data-driven decision-making at the edge and that can scale with a business’ needs is paramount to making the most of legacy assets. With this much at stake, it is no wonder that technologists at businesses of all types desire to understand how to make their edge data and legacy equipment solution a success.