Tamma V. Prabhakar

COMMON-Sense Net: Improved Water Management for Resource-Poor Farmers via Sensor Networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology

PIR sensors: characterization and novel localization technique

Pyroelectric Infra-Red (PIR) sensors are used in many applications including security. PIRs detect the presence of humans and animals from the radiation of their body heat. This could be used to trigger events, e.g., opening doors, recording video, etc. PIRs are used widely because of their low power consumption. Hitherto, PIR sensors were used for binary event generation -- human/animal present or not-present. At the same time simple binary output hinders the use of PIR sensors in a wide variety of sophisticated applications. In the literature, we find limited characterization of analog output from PIR sensors that could provide much more information. We built a simple array of PIR sensors and packaged them in a tower. We used two sets of four PIR sensors and tapped their analog signals after amplification. Our major contribution is the characterization of analog signals from the PIR sensors. We describe many interesting aspects obtained from the analog signals, which have not been explored until now. We also show their correspondence with the range, speed and size of the moving object. Using the characterization of PIR sensors analog data as well as simple binary decisions from these PIR sensors, we: (i) classify moving object with high precision; and (ii) localize the moving object. The major incentives are low operating power compared to WSNs. We achieve 30 cm accuracy in 80% of the times, when ranging up to 5 m. Over multiple experiments for different persons in the range 1--10 m, we show that the error probability for localization is 0.08 at moderate distances (around 5--6 m). Our work will help in designing better detection and application triggers using PIR sensors in the near future. We believe that this work will open up new avenues in the development of new applications with PIR sensors.

Providing security in energy harvesting sensor networks

In this work, we study the adaptability of well known cryptography algorithms to energy harvesting wireless sensor networks. We are particularly interested in algorithms that have the ability to adapt to varying power in such networks. Our investigations and implementation on hardware platforms indicate that it is optimal to precompute a few key stream bytes, store in memory and later used during the time when the system is low on harvested power level. Our demonstrable setup shows using a precomputed key stream can decrease the energy consumption by 14%. We have implemented the Trivium stream cipher for two different microcontrollers, the MSP430 and the AVR ATmega1281 and show the performance results for these implementations. We have implemented an algorithm based on universal hash functions to provide message authentication with the assistance of stream ciphers. We show that this authentication algorithm has exciting properties for energy harvesting system and more generally for resource constrained devices.

Smart applications for energy harvested WSNs

A Wireless Sensor Network (WSN) powered using harvested energies is limited in its operation by instantaneous power. Since energy availability can be different across nodes in the network, network setup and collaboration is a non trivial task. At the same time, in the event of excess energy, exciting node collaboration possibilities exist; often not feasible with battery driven sensor networks. Operations such as sensing, computation, storage and communication are required to achieve the common goal for any sensor network. In this paper, we design and implement a smart application that uses a Decision Engine, and morphs itself into an energy matched application. The results are based on measurements using IRIS motes running on solar energy. We have done away with batteries; instead used low leakage super capacitors to store harvested energy. The Decision Engine utilizes two pieces of data to provide its recommendations. Firstly, a history based energy prediction model assists the engine with information about in-coming energy. The second input is the energy cost database for operations. The energy driven Decision Engine calculates the energy budgets and recommends the best possible set of operations. Under excess energy condition, the Decision Engine, promiscuously sniffs the neighborhood looking for all possible data from neighbors. This data includes neighbors energy level and sensor data. Equipped with this data, nodes establish detailed data correlation and thus enhance collaboration such as filling up data gaps on behalf of nodes hibernating under low energy conditions. The results are encouraging. Node and network life time of the sensor nodes running the smart application is found to be significantly higher compared to the base application.

A distributed smart application for solar powered WSNs

Energy harvesting (EH) is a major step in solving the critical issue of availability of energy for sensor nodes. However, it throws many challenges. The applications built on the sensor networks powered by EH need to adapt their operations yet serve the purpose. We propose a distributed smart application for a multihop sensor network and in general in the future Internet of Things (IoT) where a network node executes an optimal number of policies to minimize the difference between available energy and consumed energy (called residual energy) for the execution of an application policy . We formulate this as a multi-criteria optimization problem and solve it using linear programming Parametric Analysis. We demonstrate our approach on a testbed with solar panels. We also use a realistic solar energy trace with a three year database including seasonality. The smart application is capable of adapting itself to its current energy level as well as that of the network. Our analytical results show a close match with the measurements conducted over testbed.

Sensor Network Deployment For Agronomical Data Gathering in Semi-Arid Regions

We share our experience in planning, designing and deploying a wireless sensor network of one square kilometre area. Environmental data such as soil moisture, temperature, barometric pressure, and relative humidity are collected in this area situated in the semi-arid region of Karnataka, India. It is a hope that information derived from this data will benefit the marginal farmer towards improving his farming practices. Soon after establishing the need for such a project, we begin by showing the big picture of such a data gathering network, the software architecture we have used, the range measurements needed for determining the sensor density, and the packaging issues that seem to play a crucial role in field deployments. Our field deployment experiences include designing with intermittent grid power, enhancing software tools to aid quicker and effective deployment, and flash memory corruption. The first results on data gathering look encouraging.

Simulation blocks for TOSSIM-T2

We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor. The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio, LEDs, and external flash memory. Using the manufacturerpsilas data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

Murphy loves CI: Unfolding and improving constructive interference in WSNs

Constructive Interference (CI) phenomenon has been exploited by Glossy, a mechanism for low-latency and reliable network flooding and time synchronization for wireless sensor networks. Recently, CI has also been used for other applications such as data collection and multicasting in static and mobile WSNs. These applications base their working on the high reliability promised by Glossy regardless of the physical conditions of deployment, number of nodes in the network, and unreliable wireless channels that may be detrimental for CI. There are several works that study the working of CI, but they present inconsistent views. We study CI from a receivers viewpoint, list factors that affect CI and also specify how and why they affect. We validate our arguments with results from extensive and rigorous experimentation in real-world settings. This paper presents comprehensive insights into CI phenomenon. With this understanding, we improve the performance of CI through an energy-efficient and distributed algorithm. We cause destructive interference on a designated byte to provide negative feedback. We leverage this to adapt transmission powers. Compared to Glossy, we achieve 25% lesser packet losses while using only half of its transmission power.

An animation-and-chirplet based approach to intruder classification using PIR sensing

The development of a Passive Infra-Red (PIR) sensing based intrusion detection system is presented here having the ability to reject vegetative clutter and distinguish between human and animal intrusions. This has potential application to reducing human-animal conflicts in the vicinity of a wildlife park. The system takes on the form of a sensor-tower platform (STP) and was developed in-house. It employs a sensor array that endows the platform with a spatial-resolution capability. Given the difficulty of collecting data involving animal motion, a simulation tool was created with the aid of Blender and OpenGL software that is capable of quickly generating streams of human and animal-intrusion data. The generated data was then examined to identify a suitable collection of features that are useful in classification. The features selected corresponded to parameters that model the received signal as the super-imposition of a fixed number of chirplets, an energy signature and a cross-correlation parameter. The resultant feature vector was then passed on to a Support Vector Machine (SVM) for classification. This approach to classification was validated by making use of real-world data collected by the STP which showed both STP design as well as classification technique employed to be quite effective. The average classification accuracy with both real and simulated data was in excess of 94%.

Near Field Communication – Applications and Performance Studies

Near Field Communication (NFC), is an integration of Radio Frequency Identification (RFID) technology with mobile devices. NFC offers a quick and convenient method of interaction between humans and NFC enabled devices. Current research concerning NFC appears to mainly focus on development of NFC enabled applications and services. In this paper, we study the performance of NFC devices by considering metrics such as achieved data rates and received power for several distances. Knowledge of these metrics may be useful for application developers to build applications efficiently. We have developed various applications on NFC enabled devices for public transport systems. We also describe the design of 13.56 MHz antenna which was used for measurements of the received power.