Energy-Harvesting Wireless Sensor Nodes Enable an Internet of Things

 

As the Internet evolves, communication is no longer predominantly between users.

Machines have begun generating and consuming content and this trend is accelerating massively. The Internet of Humans is increasingly being complemented by an Internet of Things (IoT) providing a wealth of new information and enabling new forms of automation. But the communication in the IoT has specific requirements. Energy harvesting wireless sensor nodes can meet these demands.

With the IoT and IPv6 users will be able to directly access data related to the current situation, followed by calculations in real time and the intelligent control of actuators.

The necessary networks built of sensors, actuators and processors can be composed and flexibly modified according to the actual demand. In the process, data storage and processing can be done locally or within a cloud-based infrastructure (Infrastructure as a Service – IaaS). Hence, a user instructs the heating system over the Internet to raise the temperature to comfort level ahead of returning home. Here, the content or the command respectively is generated by the human being, whereas the heating system processes the data and turns up the heating in a specific period of time. Additionally, wireless sensors measure outdoor and room temperature which, together with the current weather forecast, can be used by the home automation system to calculate the required heating. Machines (sensors, actuators, control units) now communicate directly with users or other machines on a broad scale over the Internet.

Benefits of an internet of things

Having a large network of sensors, actuators and control units all interacting with each other and the user can bring several distinct benefits.

More input (sensor) data usually yields a better insight into the system status. This additional information allows a better decision-making process considering a broad range of criteria. Examples, where this is true, include industrial process control and automation, structural monitoring and agriculture. Unlike the standard approach of one or more sensors being connected to one central control unit, an Internet of Things allows the sharing and reuse of available information between different partners. Thus, the system collects data only once but uses the information for several applications.

Current control systems are usually local; for example sensors, control unit and actuators are often in close proximity and directly connected with each other (wired or wireless). An Internet of Things no longer requires such proximity. It allows centralised, or even outsourced computing resources (cloud-based computing), thus driving down infrastructure cost. The IoT also allows a dynamic creation of control networks. The networks can be formed or dissolved dynamically based on time, location or other parameters. For instance, cars could automatically query temperature sensors in the street to determine if there is a danger of ice on the roads and warn the driver accordingly. These examples illustrate the enormous potential that can be unleashed by an Internet of Things. All the required base technologies for forming such network already exist today – sensors, actuators, local or cloud-based control units and IPv6 to connect all of them together.

Requirements for a connected world

  • Computing power is readily available both locally or cloud-based. The main challenge is how to deploy large numbers of sensor and actuator nodes and connect them in a suitable way.
  • Installation: large numbers of new sensor and actuator nodes need to be deployed (often in an existing infrastructure).
  • Scaling up in the number of deployed units due to expansion etc.
  • Service and maintenance required by individual nodes have to be minimal when creating large scale networks. The vast majority of nodes in such networks needs to be maintenance-free.
  • Communication between all parties involved has to be rolled out. A true Internet of Things can only be formed if all of its nodes can be accessed via Internet Protocol (IP). It is not required that the nodes themselves physically communicate via IPv6 as long as the translation between the node’s protocol and IPv6 is transparent. At the same time, secure data exchange is a key consideration when sensor information and actuator commands are exchanged over the Internet.
  • Finally, the cost is almost always a limiting factor, so the total cost of ownership must be low. These requirements can all be met by wireless systems giving ease of installation and scalability. Maintenance-free, zero cost of operation sensor and actuator nodes can only be achieved via energy harvesting wireless sensor nodes.

Energy sources

There are three main categories of energy that are typically used for self-powered energy harvesting devices.

Solar energy

The energy of ambient light can be converted to electrical energy using miniaturized solar cells.

Kinetic energy

The energy of lateral movement, rotation or vibration can generate electrical energy using electromagnetic or piezoelectric harvesters.

Thermal energy

The energy of close distance temperature differences can be converted to electrical energy with Peltier elements.

Additional, less widely used, ambient energy sources include electromagnetic waves as well as chemical and bioelectric systems. The key challenge with all these energy sources is that they provide very small amounts of energy. Energy release can occur either in short bursts or as a continuous trickle. In both cases, it typically needs to be accumulated and often converted (to higher voltage levels) to be usable. This places significant challenges on the design of energy harvesting wireless sensor nodes. Specifically, such devices need to have a very energy efficient system design using a very low duty cycle (devices are sleeping most of the time) and requiring only extremely low standby currents while sleeping. The communication protocol used by such devices needs to be optimised for energy efficiency to minimise their active time.

Energy-efficient system design

Since most energy harvesters deliver only very small amounts of power, it is necessary to accumulate it over time while the system is sleeping and to lose only a small fraction of it in the process.

Therefore, the most fundamental requirement for such energy- efficient systems is that they have an extremely low idle current. This means that only a very tiny amount of energy is consumed while the system is sleeping. Standard consumer electronics devices today have a standby current in the range of a few milliamperes (mA), whereas power-optimised embedded designs typically achieve standby currents in the range of a few microamperes (uA), an improvement of factor 1,000. In comparison, the latest generation of EnOcean energy harvesting wireless sensors require standby currents of 100 nanoamperes (nA) or less, an improvement of more than factor 10,000. Achieving this level of performance requires very advanced design techniques and extensive optimisation of each individual component. The second requirement is that the accumulated energy has to be used as efficiently as possible when the system is in active mode. For wireless sensor devices, the two main tasks in active state are to measure an external quantity and to wirelessly transmit information about its value. Both tasks need to be optimised for minimal power consumption. In the case of a wireless transmission, this means that the chosen protocol must be as effective as possible. The payload associated with sensors is often small (a few bytes), therefore the protocol overhead must be limited as much as possible.

This latest requirement is difficult to achieve using IPv6 as a communication protocol even at the individual sensor level because it incurs significant overhead; the IPv6 header alone requires 40 bytes of protocol data (Figure 1). In addition to that, UDP – probably the simplest communication protocol on top of IPv6 – would require an additional 8 bytes of protocol data (Figure 2). Based on the IPv6 and UDP header structure, the transmission of 1-byte sensor data would require an additional 48 bytes of low level protocol data. IPv6/UDP is therefore not well suited for Energy-efficient communication at a sensor level in a network. In comparison, the industry-leading EnOcean protocol for energy harvesting wireless applications in accordance with ISO/IEC 14543-3-10 would incur only 7 bytes of protocol overhead for the transmission of 1 byte of sensor data (Figure 3). Translation between such an energy-efficient sensor protocol and IPv6 is provided by dedicated IP gateways that represent the state of each connected sensor node and act as their representative within the IPv6 network.

Foundation for IoT

This integrated approach of protocol translation enables all parties to communicate with energy harvesting wireless sensor and actuator networks via IPv6.

That way, a protocol such as ISO/IEC 14543-3-10, which is optimised for ultra-low power and energy harvesting wireless applications, can be used for the communication between the sensor and the gateway. This allows the deployment of a broad range of maintenance-free and cost-effective devices which are wirelessly connected.

In conjunction with IPv6 gateways, these nodes will form the foundation of the Internet of Things and enable the next technology revolution. A good example of such an implementation is Raspberry Pi coupled with EnOcean Pi. This gives users an IP gateway that will interact with any EnOcean Ecosystem whilst preserving an IP backbone. Using the Raspberry Pi a user can load open software such as OpenHab to give simple access to IP to EnOcean communications. Open- Hab like the EnOcean Alliance is a member of the AllSeen Alliance which with its AllJoyn gives a collaborative open-source software framework that makes it easy for developers to write applications that can discover nearby devices, and communicate with each other directly regardless of brands, categories, transports, and operating systems.

This approach allows exchanging data with individual sensors even while they are sleeping and therefore unavailable for direct communication. Upon wake-up, sensors will then update their state information in the gateway and retrieve messages/commands intended for them.

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