Debraj Basu

Wireless sensor network based smart home: Sensor selection, deployment and monitoring

The ubiquitous nature of miniature wireless sensors and rapid developments in the wireless network technology have revolutionized home monitoring and surveillance systems. The new means and methods of collecting data efficiently and have led to novel applications for indoor wireless sensor networks. The applications are not limited to solely monitoring but can be extended to behavioral recognition. This can be of great value with the elderly as it can allow anomalous behavior to be detected and corrective actions taken accordingly. This paper details the installation and configuration of unobtrusive sensors in an elderly persons house - a smart home in the making - in a small city in New Zealand. The overall system is envisaged to use machine learning to analyze the data generated by the sensor nodes. The novelty of this project is that instead of setting up an artificial test bed of sensors within the University premises, the sensors have been installed in a subjects home so that data can be collected in a real, not artificial, environment.

Towards a monitoring smart home for the elderly: One experience in retrofitting a sensor network into an existing home

There has been a lot of research interest in research smart homes for behaviour recognition and related tasks supporting the elderly living alone. Amongst the many challenges of such research are the selection of sensors and the secure storage of data. However, there are other important issues such as reliable data collection, acceptance of sensor systems into the inhabitants life, and ensuring that the sensor system does not create hazards in the house.In this paper we report on our experiences retrofitting a set of wireless sensors into the house of an elderly person living alone and an exploration of some of the data integrity issues faced.

Protocol for improved energy efficiency in wireless sensor networks to support mobile robots

In this paper we propose a low cost and computationally inexpensive adaptive transmission power control algorithm for wireless sensors to communicate with the base station or hub. This power control algorithm can be used in scenarios where the transmitting station is not static and the distance between the transmitter and the receiving station changes with time. In addition to that there can be unwanted obstructions in between the transmitter and the receiver. Since the primary reason for drop in received signal strength is distance, it is important to select a set of power levels that will deliver the packets within a threshold error rate while saving energy. This adaptive algorithm does not use received signal strength indicator (RSSI) based beacon or probe packet for channel estimation nor listens for any busy channel before actual packet transmission. The hardware used for evaluating the protocol parameters is nRF24L01+ transceiver module from Nordic Semiconductor Inc. This chip is extremely cheap and the application of the adaptive power control protocol can reduce the overall deployment cost of sensor network. This algorithm is designed to meet the challenge of responding to an unknown and variable radio channel in an energy-efficient manner. The adaptive protocol uses past transmission experience or memory to decide the power level at which the new packet transmission will start. This lightweight protocol can be applied in mobile robots that collect data in real time from sensors and transmit to the base station.

Performance Comparison of a Novel Adaptive Protocol with the Fixed Power Transmission in Wireless Sensor Networks

In this paper, we compare the performance of a novel adaptive protocol with the fixed power transmission protocol using experimental data when the distance between the transmitter and the receiver is fixed. In fixed power transmission protocol, corresponding to the distance between the sensor and the hub, there is a fixed power level that provides the optimal or minimum value in terms of energy consumption while maintaining a threshold Quality of Service (QoS) parameter. This value is bounded by the available output power levels of a given radio transceiver. The proposed novel adaptive power control protocol tracks and supersedes that energy expenditure by using an intelligent algorithm to ramp up or down the output power level as and when required. This protocol does not use channel side information in terms of received signal strength indication (RSSI) or link quality indication (LQI) for channel estimation to decide the transmission power. It also controls the number of allowed retransmissions for error correction. Experimental data have been collected at different distances between the transmitting sensor and the hub. It can be observed that the energy consumption of the fixed power level is at least 25% more than the proposed adaptive protocol for comparable packet success rate.

Investigation into the impact of protocol design on energy consumption of low power wireless sensors

This paper proposes a modified communication protocol that uses the knowledge of channel states to transmit packets. It shuts off the energy expensive acknowledgement operation during good channel state while uses all its retransmission attempts in bad channel state to deliver the packets through the channel. The impact of this protocol has been directly studied on the coin cell batteries that are used to power wireless sensors by emulating the loads for the battery and radio channel conditions. The radio channel is modeled as two state Markov chain with FAVORABLE and NON-FAVORABLE states. Three different channel conditions - good, bad and uncertain - are considered based on how often they transit between the FAVORABLE and NON-FAVORABLE states. The results have been compared with a classical communication protocol where communication between nodes takes place on send-acknowledge basis with a fixed number of retransmission attempts when error occurs. Our proposed protocol shows promising improvement in battery lifetime when dealing with good channel and found to be more effective in the other two channel conditions when the receive operation time is high. Analytical results are also used to substantiate our observations.

Novel Adaptive Transmission Protocol for Mobile Sensors that Improves Energy Efficiency and Removes the Limitation of State Based Adaptive Power Control Protocol (SAPC)

In this paper, we have presented a novel transmission protocol which is suited for battery-powered sensors that are worn by a patient when under medical treatment, and allow constant monitoring of health indices. These body-wearable sensors log data from the patient and transmit the data to a base-station or gateway, via a wireless link at specific intervals. The signal link quality varies because the distance between the patient and the gateway is not fixed. This may lead to packet drops that increase the energy consumption due to repeated retransmission. The proposed novel transmission power control protocol combines a state based adaptive power control (SAPC) algorithm and an intelligent adaptive drop-off algorithm, to track the changes in the link quality, in order to maintain an acceptable Packet success rate (PSR)(~99%). This removes the limitation of the SAPC by making the drop-off rate adaptive. Simulations were conducted to emulate a subject’s movement in different physical scenarios—an indoor office environment and an outdoor running track. The simulation results were validated through experiments in which the transmitter, together with the sensor mounted on the subject, and the subject themselves were made to move freely within the communicable range. Results showed that the proposed protocol performs at par with the best performing SAPC corresponding to a fixed drop-off rate value.

A distributed mechanism for Software-based mobility management

A network-assisted mobility management scheme has been proposed in this work for a Software-Defined Network (SDN). Instead of using just one controller as is the case in the legacy SDN, this work explores a distributed architecture with multiple sub-controllers. Detailed procedures for intra-domain and inter-domain handovers under this setting have been introduced and explained.

Effectiveness of a Novel Power Control Algorithm in Heart RateMonitoring of a Mobile Adult: Energy Efficiency Comparison with FixedPower Transmission

In this paper, experiments are conducted to evaluate the efficacy of a novel adaptive power control algorithm in terms of energy efficiency in heart rate monitoring scenario of a mobile adult in a typical home environment. As part of health care, persons with heart related problems are required to be monitored by logging for example, their heart rate on a regular basis to check for any anomaly. At the same time, it is expected that the person in question should be able to move freely within the given facility. The wireless sensors that are attached to the person send periodic data to the central base station. Since the person is mobile, the distance between the transmitting sensor and the base station changes with time. Since the signal path-loss is primarily dependent on distance and the number and type of obstructions between the transmitter and the receiver, it may be wise to use transmission power control to modulate the transmit power. Using power control, the sensor can adjust the level that is sufficient to send the data through the wireless channel without wasting energy. Conservation of energy is critical in wireless sensor network scenarios because they are powered by batteries which have limited lifetime. A critical application like the heart rate monitoring sensor is expected to operate for a reasonable amount of time before the battery dies. The novel adaptive power control algorithm uses intelligent modulation methods to ramp up or ramp down the transmission power level as and when required. By this method, the operational lifetime of the wireless sensor can be extended. As part of the experimental methodology for this paper, two subjects of different age groups have been used. Experimental results show that there is at least a 12% increase in the energy savings using the proposed algorithm.

Energy Efficiency Comparison of a State Based Adaptive Transmission Protocol with Fixed Power Transmission for Mobile Wireless Sensors

In this paper a state-based adaptive power control protocol (SAPC) has been compared with classical fixed power communication for mobile wireless sensors. The distance between the transmitter and the base station is often not fixed as in the case of body wearable sensors. There can also be unaccounted obstructions in between the transmitter and the receiver. Since signal level attenuates with distance, it is important to choose the right power level that will not only deliver the packets with minimum error but conserve energy at the same time. The proposed adaptive algorithm does not transmit beacon or probe packet for channel quality estimation using the received signal strength before transmitting actual packets. It uses the present and past history of the outcome of packet transmission to evaluate and track link quality. The unique SAPC algorithm also controls the number of re-transmissions in each state. Experimental validation has been done using nRF24L01p transceiver modules. This algorithm can adapt itself to an unknown and variable radio channel in an energy-efficient manner. Experiments were conducted in indoor office environment within a university building and results show that SAPC uses up to 30% less energy than the fixed power communication

A Wi-Fi based passive technique for speed estimation in indoor environments

The conventional positioning systems require the users to carry an electronic device, which helps in the localization process. Device-free Passive Localization (DfPL) techniques are used to position the users in a passive manner such that they do not engage in the process. A typical DfPL setup comprises of Wi-Fi Access Points (APs) that transmit periodic signals to Monitoring Points (MPs). Any intrusion within the area of interest is detected by constantly examining the strength of Wi- Fi signals received at MPs. In this paper, we examine DfPL using 1 AP and 1 MP to estimate the speed of motion in a given indoor area. The proposed method is shown to achieve high accuracy.