There is a huge demand today for adding Wi-Fi connectivity to IoT applications because of the many advantages over other wireless protocols (Zigbee, Bluetooth, etc.) such as longer range, native IP connectivity, and high bandwidth. For millions of IoT applications, including industrial machines and sensors, Wi-Fi is often the best choice for connectivity because of its robust infrastructure and global reach- Wi-Fi exists almost everywhere in the world today.
Challenges for developers: The biggest challenge for developers has been the high-power consumption of Wi-Fi in IoT systems. Wi-Fi protocols were designed primarily to optimize bandwidth, range, and throughput, not power consumption. This makes it a poor choice for power-constrained applications that rely on battery power. Of the various cons of using standard Wi-Fi protocols, high power consumption is the most impactful (range limitations and busy networks are cons as well). Until today, developers have avoided adding Wi-Fi to their IoT applications as there hasn’t been a viable option for adding Wi-Fi connectivity to battery operated devices that didn’t require high power consumption.
These are the four key challenges when adding Wi-Fi connectivity:
Power consumption in Wi-Fi varies dramatically across various modes of operation and it’s important to understand the different modes and optimize them to reduce overall power consumption. One strategy is to stay in the lowest power mode as much as possible and transmit/receive data quickly when needed.
RF performance: Unlike many wireless protocols, Wi-Fi power consumption is significantly impacted by RF performance and network conditions. This is a significant problem with the increasingly crowded Wi-Fi networks today. A busy network leads to many retries/retransmissions which consumes a high level of power. Developers must focus on reducing retransmissions and controlling link budgets to be successful.
Wi-Fi devices typically consume significant power in both Transmit (Tx) and Receive (Rx) modes. There are several ways to reduce power consumption and optimize Tx and Rx modes. First choose devices with high selectivity/out of band rejection. Also, choose devices with high Rx sensitivity, and if possible, choose uncrowded channels for device operation. This might mean using channels not used by chatty connections such as video streaming.
Applications: Power consumption is highly dependent on the application and use case. IoT applications typically fall into one of three categories:
Always on/connected-these devices are always on which allows users to access the device remotely at any time via cloud or mobile application. A Wi-Fi video camera is a good example of this use case. Latency is a critical factor in these applications and power consumption is dominated by the transmit power mode (the highest power consumption), as the device is transmitting data and it would be detrimental to be inactive or inaccessible.
Periodically connected - These devices are connected to a remote server or cloud platform and only need to transmit occasionally. A good example is a temperature or humidity sensor that sends data every few minutes and it can tolerate the small amount of time it takes to become active. Latency is not a major concern and the power consumption is dominated by receive and sleep currents. It stays in intermediate power levels so it’s never completely awake or asleep so it wakes up faster.
Event-driven - An online shopping order button is a good example of event-driven Wi-Fi connectivity. It’s almost always inactive/asleep, meaning there is no data transmission. It wakes up infrequently, and it takes longer to wake up from this mode. An event occurs that triggers wakeup such as when a user selects the order button. This mode is dominated by the lowest sleep current and is best when needing to use the least amount of power possible for an IoT application.
Design issues - Lowering Wi-Fi power consumption is also a design system issue and is a critical challenge for developers today. Power management and extended battery life are major factors when developing IoT applications. Although standard Wi-Fi protocols weren’t designed initially for low power operations, there are many techniques to help significantly reduce power consumption. These techniques include optimizing Rx and Tx modes, optimizing power-saving modes (sleep modes, WMM, DTIM, shutdown/standby), choosing the right hardware, using built-in specifications, optimizing RF performance, and system level optimization. Developers must understand all the contributing factors to overall energy consumption in IoT devices.
They must also understand both system-level factors and deep application factors in order to achieve low energy consumption in their applications. Finding the right mix of power-saving Wi-Fi modes and selecting the right hardware are the keys to dramatically reducing power consumption. Leveraging hardware and software designed specifically for IoT devices and low power consumption can reduce long term costs, overcome development challenges, extend battery life, and potentially enhance the life of products and customer satisfaction.
We solve the power management issues for IoT developers by providing drop-in Wi-Fi solutions, including pre-programmed modules (WF200 and WGM160) that can cut power consumption in half. These solutions are designed proactively with low power IoT applications in mind and work in a wide range of applications from home automation to commercial, retail, security, and consumer health-care products. Pre-programmed modules provide a prototype quickly which helps developers get products to market faster.
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