Wireless Sensor Technology Advances

Wireless sensors are measuring equipment with a transmitter that can measure conditions such as temperature, pressure, sound, pH, flow, etc. These sensors receive the signals from the process control instruments, converted into radio broadcasts through transmitters. The radio signals are sent to a receiver, which receives them and uses computer software to transform them to the appropriate output (analogue current, contact closure, or digital display).

Wireless Sensor Technology has several advantages, including safety, cheap cost, and simplicity. It is seeing increasing demand from industrial and consumer uses, which is driving new advances.

Wireless Sensor Technology Advances in the Last Few Years

Wireless Energy Efficiency Sensors at a Low Cost

Researchers at the US Department of Energy’s Oak Ridge National Laboratory (ORNL) have created a low-cost, energy-efficient wireless sensor prototype that can cut building energy use by 20 to 30%.

In addition, in contrast to affordable traditional wired sensors, gathering data such as room temperature, light level, air quality, humidity, and contaminants is often costly, ranging from $150 to $300 per node wireless sensors. ORNL’s wireless sensors, on the other hand, use a roll-to-roll manufacturing approach to cut the cost from $1 to $10 per node. These fantastic sensors gather data from many nodes and deliver it to a receiver, which then sends it to the energy-intensive system. This technology can also help with issue detection and service management.

Wearable Biosensors for Obesity Monitoring

Mayo Clinic, a nonprofit medical research organisation located in Rochester, collaborates with Gentag, a company based in the United States, to develop novel biosensor technology to combat two critical health problems: obesity and diabetes.

The patch biosensor, which is the size of a bandage, would be the first wearable sensor capable of monitoring a patient’s health. This wireless, disposable wearable comprises a sensor that communicates with a diabetes management system compatible with a smartphone and gives researchers the essential data while also assisting with treatment developments.

Self-powered Building Fault Detection Sensors

Researchers at Michigan State University’s College of Engineering are developing a new substrate computing technology that can detect and warn authorities about concerns with a bridge or a dam. It is beneficial to future constructions. This technology will function by embedding small 3mm-by-3mm electrical chips into a structure’s construction material. “Our goal is to use fault detection sensors in building materials that can monitor and report on structural issues,” explains electrical and computer engineering professor Subir Biswas.

Integration of Libelium Sensors with Microsoft Azure Cloud to Accelerate TTM

Libelium and Microsoft unveiled Microsoft Azure Cloud integration with Waspmote Wireless Sensors at Mobile World Congress on March 2, 2015, to reduce time-to-market (TTM). Polibol, a packaging maker, will benefit from the combination. The Waspmote Plug & Sense! Wireless sensors, Meshlium gateway, and Microsoft Azure cloud computing platform monitor critical processes and provide information about environmental variables related to the factory and several parameters that may affect the working condition and quality of the product. Sensor technology can help organisations cut expenses and enhance productivity by measuring energy consumption, environmental concerns, and water quality.

Sensor network technology in the solution allows gathered data to be sent straight to the cloud from sensor nodes. Polibol employees may also handle real-time variables using a smartphone, computer, or tablet with an internet connection.

Types of Sensors Sensors are at the core of any WSN. Multiple sensing technologies have advanced rapidly in the last decade: 

• Microelectromechanical systems include gyroscopes and accelerometers (MEMS).

• Temperature, humidity, capacitive proximity, and chemical composition sensors based on CMOS 

• LED sensors – measuring ambient light, proximity, and chemical composition. These low-cost sensors offer new applications like enhancing HVAC management and lighting in homes and buildings when connected via a network. 

In 2010, HVAC and lighting used 48.1% of company energy. According to the US DOE’s “Annual Energy Outlook 2012” report, most of it is wasted due to the absence of smart systems.

Most HVAC and lighting systems are on timers and do not account for human presence. Using MEMS, CMOS, and LED sensors to measure environmental variables (humidity, temperature, ambient light) and human presence may substantially decrease total power utilisation (pyroelectric, proximity, and acoustic). Once a sensor network is constructed, more features may be added. Acoustic sensors can detect smashed glass from a suspected late-night break-in and monitor human physical presence throughout the day.

Another example is utilising human presence information to remove power from wall outlets to avoid “vampire power” pulled by powered devices (e.g., computer monitors, TVs, etc.) while people are not present. According to experts, vampire power accounts for 7-15 percent of business energy use. Advances in Semiconductor Technology The hardware necessary to enable large-scale WSN applications eventually achieved competitive pricing thresholds when the semiconductor industry started standardising on CMOS processing technology for most semiconductor components by the late 1990s. Network designers no longer use discrete circuits or multi-chip solutions because they are too big and power demand.

Wi-Fi MCUs are system-on-chip devices that integrate a general-purpose MCU with an RF transceiver onto one chip. SoCs with high-performance peripherals (amplifiers, ADCs, DACs) and non-volatile memory may manage application processing and network protocol stack while providing RF connectivity.

Leading semiconductor suppliers now provide wireless SoCs for WSN applications. So, the EM35x Ember® ZigBee® series from Silicon Labs has an 8-bit CortexTM-M3 CPU, IEEE 802.15.4-2003 transceiver, AES encryption accelerator and sub-A sleep mode currents. To create a sensor node in a WSN, add a battery and a sensor to the EM35x SoC on an inexpensive circuit board.

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