Intelligent measurement of environmental air quality using Internet of Things Technology. We plan on designing a system for air-pollution data collection using the Internet of Things technology (IoT) thus mapping Real-time values of the noxious gases parameters. Gas content level sensor monitoring is an important product with huge international level market success potential. . The system can be installed in various industries to monitor their level of pollution. Data can be used for determining the effect of Pollution on crops and human health in terms of various agricultural and respiratory diseases.
Losses Reduction through Smart HVDS System
Losses Reduction through Smart HVDS System
HVDS system for technical loss reduction by improving ratio of HT to LT lines. When the ratio increases it causes
- Reduction in technical losses in electrical distribution system.
- Improvement in supply quality and reliability.
- Reduction in commercial losses
Causes of higher technical losses
- Improper location of distribution transformer
- Non – optimal conductor size
- Inadequate augmentation of transmission and distribution system
- Lengthy distribution lines
- Electricity theft from LT
Advantages of using HVDS
- Reduction of phase to phase fault
- Less number of consumers are affected in case of failure of smaller distribution transformer(HT lines)
- Almost impossible to connect hooks on HT network lines
Smart and Secure Electricity Billing Framework
Design and implementation of a Prototype for a Secure Billing Framework with Real Time Detection of Malicious End Node Connections using Wireless Sensor Networks to Curb Electricity Theft. Project initiated in collaboration with Peshawar Electric Power Company (PEPCO)to reduce/eliminate electricity theft that accounts for a loss of an approximate 40 Billion Rs annually. Deployment of wireless sensor modules interfaced with compact current transformers to measure and compare readings at different locations for detection of any instances of meter bypassing is currently underway. Obtain a low cost optimal design for meter reading and wireless transmission using Computational Intelligence techniques. Explore high processing capabilities of 32 bit Microcontrollers for processing of large chunks of data at the Access/Subscriber Modules (distribution point). Develop effective information dissemination algorithms to communicate the data efficiently and reliably between different modules.
Smart Detection of Gas/Oil Leakage & Theft via WSNs
Project initiated in collaboration with SNGPL to reduce/eliminate Gas theft and leakages that accounts for a loss of an approximate 40 to 60 Billion rupees annually. Deployment of wireless sensor modules to measure and compare readings at different locations for detection of any instances of meter bypassing is currently underway. Obtain a low cost optimal design for meter reading and wireless transmission using Computational Intelligence techniques. Develop effective information dissemination algorithms to communicate the data efficiently and reliably between different modules.
Continuous monitoring system along any highway route for a breach and its reporting in real-time along with vehicle tracking to detect and report un-desired activities or faults. Real time monitoring of the Infrastructure ensures security and enhances its utilization. We are providing a low cost and robust solution (Lesser capital and runtime cost). An ideal solution for highways, motor-ways and border control. It will help in real time Traffic Scheduling
Smart Disaster (Flood) Management System Using WSNs and Machine learning
The System aims at planning and management of floods using real time information management system and efficient artificial intelligence models. It also identifies areas prone to floods through Wireless Sensor Networks (WSNs). Additionally it aims at designing and manufacturing of sensors and development of appropriate distribution architecture to monitor the areas for the prediction of potential flooding followed by the training of the prediction system for future use.
The safe roads concept stems from the idea of safeguarding every individual car traveling within a city from car napping, passengers/driver kidnaping, or any kind of robbery or malicious threat to its passengers. A car owner on paying a certain fee will have a small camera with a secret button installed in the car. In case of any imminent threat to his life or car from any person he will press a secret button which will turn on a live feed. This live feed along with the cars GPS locations will be sent to a control center. The control center will accordingly inform the relevant authorities regarding the situation in the car. This is more suitable for passenger busses, where various malicious activities of passengers can be monitored and the live feed of the active bus will be transferred to the control center avoiding any terrorist threats.
Intelligent Transportation System (ITS)
A Secure and Intelligent Transportation System using Wireless Sensors for congestion control to investigate, develop and implement the most appropriate queuing theory algorithms to prioritize queues (traffic lanes) based on the gathered real time traffic data and alleviate congestion by autonomously controlling the traffic signals through an installed Decision/Control unit. Develop a feasible criteria to prioritize traffic lanes as well as certain vehicles e.g. ambulances, law enforcement vehicles in pursuit etc. Research a feasible multi-radio/multi-channel communication technique to allow multiple RFID readers to report to a central control/decision making unit that embeds the queuing theory algorithm for real time-on the spot decision making.
Safe City-Machine Learning takes the concept of safe city one step further by introducing artificial intelligence to it. Human eye is susceptible to error and human beings while monitoring CCTV cameras can be prone to miss a problematic event. Thus we propose a system where the images from the CCTV camera are taken and a prediction model evolved on previous such images is used to detect further mishaps. The model is continuously evolving to further improve its detection capability. Safe City-ML will incorporate smart machine learning management to detect an event automatically from many images. The system working for a safe city will automatically generate alerts for an operator with the image of the problematic area who then calls on the concerned authorities and nearby law enforcement vehicles in case of any law and order or other situation requiring attention An intelligent transportation system to curb congestion and make inner city roads safe and protected will also be incorporated through sensor monitoring along with CCTVs for scheduling the traffic. Safe City-ML will also have safe homes, safe schools, safe colleges, safe government institutions where continuous monitoring will be done through sensory network, automated reports on various malicious activities and events will be directed to the central and regional monitoring stations..