Tsung-Han Lin

A measurement study of zigbee-based indoor localization systems under RF interference

With an expected market value of 2.71 billion in 2016, supporting daily use of real-time location systems in households and commercial buildings is an increasingly important subject of study. A growing problem in providing robust indoor location estimations in real time is the use of wireless transmissions in RF frequencies. Having implemented a simple RSSI-signature-based location system on a 24-node IEEE 802.15.4-based sensor network testbed, we are able to analyze the effect of background IEEE 802.11 traffic on localization error. The measurement results demonstrate that the 80th-percentile of the localization error may increase by 141% at worst in an office building with active use of IEEE 802.11 for data. Such performance degradation results from RSSI reading loss as the beacon messages collide with background traffic.

On the potential of sensor-enhanced active RFIDs

As the popularity of the passive RFID technology continue to surge, we see promising applications in its active counter-genre. There is however an inherently limited lifetime in any active RFID-based system because the active RFID tags operate on batteries. To hurdle through the energy limitation, we think the opportunities lie in the creative embedding and use of sensors with the active RFID tags. With a case study, referred to as the personal object alarm, we show the potential of embedding sensors to active RFID tags for optimal system lifetime and accuracy. In particular, from the range estimation sensor, we derive the relative distance and velocity of the active RFID tags on the user and object. In turn, out-of-proximity alert can be generated timely when the users personal object moves out of the predefined range. Our experiments show that with sensor-enhanced active RFID system lasts twice as long while the accuracy of the alert is improved by 47%, in comparison to a system without any embedded sensors.

Energy-Efficient Boundary Detection for RF-Based Localization Systems

Boundary detection is a form of location-aware services that aims at detecting targets crossing certain critical regions. Typically, a lower location sampling rate contributes to a lower level of energy consumption but, in the meantime, delays the detection of boundary crossing events. Opting to enable energy-efficient boundary detection services, we propose a mobility-aware mechanism that adapts the location sampling rate to the target mobility. Results from our simulations and live experiments confirm that the proposed adaptive sampling mechanism is effective. In particular, when experimented with realistic errors measured from a live radio-frequency-based localization system, the energy consumption can be reduced significantly to 20 percent.

Sensor data aggregation for resource inventory applications

With the creative use of sensors, in the future, sensor networks could impact on a wide variety of applications from national security to consumer electronics. Sharing the vision and emphasizing the energy efficiency of data dissemination for resource inventory applications, we propose a novel data aggregation strategy and algorithms to obtain the population of the objects (i.e., the resource) to be sensed in the networks. With a set of cautiously validated simulations, we show that the energy consumption in applying our solution is only one third of the original case and scalable to the object population. Experimental results also show that we are able to obtain consistent lower and upper bounds at 70% and 180% of the exact population. While we show the solution works effectively for resource inventory applications, this work suggests more profoundly that there is yet design space to explore in application-specific data aggregation for energy conservation.

Impact of Beacon Packet Losses to RSSI-Signature-Based Indoor Localization Sensor Networks

We present an experimental study on an RSSI-signature-based localization system. The two major findings are: (1) Switching from a clean channel to a busy one, we observe, in our experiments, a 300% increase in the 80-percentile location estimation error; (2) RSSI value and packet reception rate are not correlated.

Enabling energy-efficient and quality localization services

Localization research has focused on improving the accuracy of pinpointing the physical location of a target. We think that the energy efficiency and the quality of the localization services (QoLS) are equally important properties of localization systems. We refer to the QoLS as the timely supply of the location information to the applications. Energy efficiency and quality are seemingly two contradictive goals in terms of determining the rate of triggering the localization systems to perform the necessary computation and communication. In that, a lower location sampling rate contributes to a lower level of energy consumption but in the meantime compromises the timeliness of acquiring the location information. Opting for energy efficient and quality localization services, we propose a mobility-aware mechanism that adapts the sampling rate to the target mobility. Results from our simulations confirm that the adaptive sampling approach is promising and effective

Emergency alarm system: prototype and experience

Finding fusion in the domain of engineering and healthcare, we propose a wearable emergency alarm system that 1) monitors continuously the activity levels of the patient and 2) detects anomalies, in particular unconsciousness, in a timely fashion to alert the caregivers of the emergencies. In this summary, we share our experience building the first prototype and the preliminary results that support the feasibility of the system and give rise to a number of design choices towards better energy efficiency and emergency event detection accuracy.