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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Silicon Labs has an unusually broad perspective of the smart home market, being we provide both chipset and wireless solutions to a vast array of global smart home customers. But what makes us especially unique is that we support most all of the major smart home connectivity protocols, and even offer solutions to help customers create their own wireless protocols. Wireless connectivity is complicated, but it’s getting remarkably easier for both designers and users as time goes by. And as it does, the smart home is getting much smarter.
The smart home market as we know it initially started in the early 2000s, and for many years, the question has always been – when is mass adoption going to happen? No one knows for sure. Yet we are confident adoption rates will increase substantially this coming year. According to Statista, there are already nearly 35 million smart homes in the U.S. in 2018, with growth expected toward 60 million homes by 2023. People have been using smart home thermostats, lighting, and security products for quite a few years now, but the smart speakers recently introduced have been an explosive driver for the smart home. More than 50 percent of smart speaker owners have gone on to buy other smart home products, and Gartner predicts that 75 percent of U.S. households will have smart speakers by 2020.
So what’s coming up in 2019 that will be different for the smart home? Silicon Labs shares some predictions below.
Professionals take a backseat: One of the shortcomings of the smart home thus far has been the tendency for people to buy the application they want, but once they get the package home, the installation is too complicated and an outside professional is required to install the device. Thanks to new highly interoperable smart home platforms, such as the Silicon Labs Z-Wave SmartStart, the installation of products is becoming surprisingly easier. Ring is a good example of a new plug and play security smart home product that just needs to be plugged in, then the user sees the application on their phone. It’s that easy.
AI and smart home unite: Wireless and mesh connectivity solutions have improved dramatically in range and power consumption in recent years, enabling low-costs sensors to be deployed across the home (and yard). No longer limited by short ranges and power constraints, ubiquitous devices are giving the smart home the ability to react intelligently to changing conditions. The smart home has already seen the first iterations of AI, otherwise known as context-aware intelligence, in consumer products, and more are on the way. A popular example is the smart thermostat that learns family preferences. New smart thermostats will sense how many people are in which rooms of the house and adjust accordingly. They will know what time of day energy prices drop and react for optimal economy.
Insurance industry adoption: More than ten years ago we saw smart home thermostat products disrupt the utility market, and we’re going to see those kinds of dynamics happen again in other markets. Smart home insurance IoT products are something to watch closely this year. Context-aware smart homes are allowing the insurance industry to move its central business paradigm from reactive claim services in to proactive loss prevention. A draft in the home can be traced to a roof in need of costly repair. Moisture in the garage can distinguish between a simple worn valve or an expensive leak in the foundation. Water Hero, an IoT product that detects a water leak in the house before it escalates, is the first of many new insurance IoT products that will continue to hit the market in the coming year.
Homes get even smarter: Some of the early smart home consumer products centered around video monitoring, yet a more sophisticated sensing is materializing. New smart home products for Aging in Place are a great example. Keeping close watch on older and more fragile family members doesn’t mean they need to be watched via obtrusive video cameras. Instead, data can be collected about elderly daily habits from invisible sensors in appliances, lights, rooms, medicine cabinets, etc. If the data shows unusual irregularities, family members can be notified.
Costs decrease, longevity increases: The beauty of a maturing technology market is as the technology advances, the costs come down, and this dynamic will be no different in 2019 for the smart home. Besides decreasing consumer costs, we’ll also see major gains in battery and low power. A truly smart environment features embedded sensing throughout the entire space, including areas where direct electrical power is either impossible or impractical. Battery operated devices are a necessary mainstay of the smart home landscape. Due to their need for continual battery replacement, service providers and end users often limit the deployment of these devices, thus limiting the life cycle of the system. The recently released Silicon Labs Z-Wave 700 platform is so efficient that it can allow battery operated devices to provide ten years of service on a single coin cell battery. We will start seeing the benefits of this battery development in the coming year as applications roll out based on the technology.
We'd love to hear about what you're expecting from the smart home market this year.