WiSmart for Industrial
Products and Applications

  • WiSmart Software
  • Serial to Wi-Fi
  • SPI to Wi-Fi
  • Thin Profile
  • UART
  • Customizable Commands
  • 802.11bgn
  • Secure Connections
  • Industrial Temp Range
  • Cloud Services Ready
  • MQTT
  • Mesh Support



If there is one thing that is true of logistics, it is that it is distributed. From the containers, to the crates, to the packages. From cars, to trains, to planes, to trucks, and ships. Everything has an asset value and is worth tracking if it gives a better picture of where things are, how they are moving, where they are moving to, what time they are expected to arrive, and how all of that impacts the ultimate arrival of materials so that everything else can be timed as accurately and confidently as possible. Imagine Wi-Fi networks through the supply chain supporting connections from the transportation vehicles and from the cargo as materials are moved around the world. Also imagine the ability to collect and map this information real time for analytics, adaptation, and event automation. Suppose a package, fitted with a Wi-Fi enabled device was able to communicate to the transportation vehicle where it needed to go, and while on a conveyor belt was able to tell the guide arms the new destination it had been assigned. Knowing the schedule of various legs out of the route, the recipient could be notified moments before the arrival – by the package itself.



With increasingly connect elements of factories, a future where distributed intelligence on and off the factory floor will enable more accurate feedback looks and optimization of resources, scheduling, and analytics. The IoT depends on factories becoming more connected and factories symbiotically count on the IoT becoming more widespread. Eventually, factories will be interconnected with other factories through the IoT allowing for even more pervasive connectedness that allows for nimble adjustments based on available real time information. Ultimately, this leads to total integration and automation which gives full visibility to all the elements (current, historical, and even forecasted) to make adjustments in real time. IoT connected containers, products, equipment, and interfaces to employee dashboards will provide for more efficient of available resources.



With Serial to Wi-Fi capabilities, many of the machines in the industrial space can be enabled to share information with other machines, control systems within a facility, human operators, and even machines and systems outside the factory (ie predictive maintenance, parts suppliers, warranty services, analysts, and more). Sensors, controllers, actuators, conveyors, and other machines will be connected and providing information that can be used locally and globally. Terms like Machine to Machine (M2M) and Industrial Internet of Things (IIoT) have been coined to broadly capture these types of communications from machines and machine elements to the larger universe of IoT connected devices and people. This is also an area where personal machines may be expected to talk together to coordinate activities such that peak energy consumption levels are not exceeded, production of inputs don’t exceed the rate of consumption capacity, or limits of rated speeds are monitored and kept from exceeding.



Once a sensor, an actuator, or indicator is enabled and available via the IoT, it becomes an object/element that can be used in any conceivable way to inform and automated process or automated system. Much like an intricate Rube Goldberg machine, very disparate elements (disparate in type, geographical location, or disparate in function) can be used to inform and influence the behavior of any other arbitrary element. Something as simple as a single moisture detector in a strategic location in a facility, could be used to assure that a process or machine does not operate and “run dry” – something that could be easily missed or overlooked by a human operator. By combining and analyzing seemingly disconnected aspects of processes or systems, unseens relationships may be identified through analytics that improve these newly automated processes and provide the basis for continuous learning systems that make use of increasingly high resolution data to squeeze incrementally more and more efficient outcomes.



Autonomous vehicles are already in the fields that leverage GPS signals to quickly, efficiently, and adaptively plant, fertilize and harvest crops at their “peak” readiness taking into account soil moisture, pH, weather forecasts, and market pricing/demand. Increasingly connected elements on the equipment provides more real-time and accurate information about the equipment itself, the production efficiency, capacity, and alerts to inform downstream consumers of the output of the agricultural operations. As the IoT enables information to find itself out of the the various silos (no pun intended) that are currently in place from farm to table, consumer needs can be used to more accurately schedule fresher and fresher produce to end up on the dinner table which should translate into higher nutritional content when produce is consumed. It might also translate into fewer pesticides, more local growing requiring less long distance transport, and sufficient profitability for “micro farms” nearer to “food deserts”. Reduced hunger around the globe is more accessible with IoT resources to leverage.