Cisco Announces IOx to Make the Internet of Things Real
Analysts predict there will be between 50-75 billion connected things by 2020. That means more than 200 connected things per person. These connected things will generates billions of terabytes of data that will make our world smarter. However, there is more to IoT than just connecting devices to the Internet. Connected things and the large volumes of data generated by them are not useful unless there is a way to transmit, store and analyze this information for intelligent decision-making in real-time.
To transmit large amounts of data, network bandwidth needs to accelerate at the same pace. The question is whether the billions of terabytes of data generated by devices on the edge of the network, say a lamppost or traffic signal, needs to be transmitted to the cloud or central hub over expensive 3G networks. The answer is: No. This situation can be resolved by enabling computing on the edge. This data is not just being collected for reporting after the fact, but for real-time actions which means delays in data latency and network delays just won’t cut it for IoT.
Today, Cisco announced IOx, an application enablement framework that will enable computing and open connectivity on the edge of the network. It is essentially an intermediate layer between the hub and the edge of that resolves the network bandwidth challenge. IOx will enable smart applications on the edge of the network that can process information collected from smart, sensor-enabled devices. The edge apps will process raw data and trigger actions in response that are either machine-generated or require human intervention. If the system is running smoothly and no unexpected signals are sensed, all captured data doesn’t need to be transmitted to the cloud over expensive network bandwidth. However, when an unexpected event is sensed meaning something is out of line, data is transmitted to the hub in order to take real-time action. Critical updates can be transmitted over 3G networks while routine updates and non-critical data can then be shared when a WiFi network becomes available. Such a distributed network resolves data latency issues, improves system reliability and results in faster response time.
Building on the “Consumerization of IT” trend of Bring-your-own-Device, IOx will enable BYOA (Bring-your-own-Application) or BYOI (Bring-your-own-Interface) for the network so any Linux-based app or interface can be run on the edge device.
Bringing distributed computing at the edge of the network will impact companies across verticals. One example is predictive maintenance for railways. The wheel bearings on a train directly impact its safe operations. Worn out wheel bearings could cause a train to derail. Yet today trains operate without full knowledge of the status of its parts. Sensors on wheel bearings monitor bearing’s health so faulty or worn-out ones can be replaced before they become a safety hazard. Incidentally, removing and replacing wheels on a train is an expensive process so unnecessary maintenance can be avoided if accurate information on wheel bearing health is available. In this scenario, all the data generated by sensors that monitor equipment status is not transmitted to the cloud. Critical information is transmitted when the sensor readings suggest proactive maintenance needs to be performed.
Imagine sensors or a video camera on a lamp post that gathers and processes information on everything that goes on a busy street as normal day-to-day events. Applications on the edge process this information to ensure everything is running smoothly and no action is needed. However, when there is congestion due to an accident, the app triggers automated information flow back to the hub. Combined with data from other edge devices as well as transactional data from back-end systems automated response is generated in real-time such as sending an emergency response team or re-routing traffic.
The real game-changer for companies will be the ability to combine real-time updates from the edge of the network with transactional back-end data to make intelligent decisions. For example, when a shopper walks into a store, sensors throughout the store and merchandise collect data on how long a he / she spent in a particular section, say denim wear, which item he/she tried on in a fitting room. Combining this information with backend data from CRM such as gender, age, past purchase history, preferences etc. allows the clothing retailer to offer highly personalized deals and discount offers – 25% off on your second pair of jeans or recommendations for matching shirts to go with the jeans you tried on. This in turn results in higher conversion rate and customer loyalty.
Here is what is needed to make the edge devices smarter and enable edge applications: embedded database at the edge that can source sensor data, store and manage it; smart applications that can process and synchronize information built using an IoT app development platform; and a CEP (Complex Event Processing) engine that processes large volumes of complex events at the edge.
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Link to Cisco Press Release: Cisco Delivers Vision of Fog Computing to Accelerate Value from Billions of Connected Devices – Jan 29,2014