In the power line industry, the phrase of keeping the lights on goes much deeper to those in the field. “Safety, Safety, Safety” is the everyday motto. Getting home every day with every finger and toe and keeping the world with access to electricity is a very dangerous job. This solution brings up many questions. How can outages be prevented and how can we keep our people safe? The main solution is by helicopter. Having a person hanging out of the bay while a helicopters fly close enough to energized lines to take pictures and taking this data and analyzing every single image that was capture to scrutinize every fine detail to detect any problems. To most, this seems to be very unsafe and very unproductive. In this modern day and age, technology has taken great leaps and need to be implemented in better ways to cut out the human factor for safety. Today there are three technologies that have different jobs but if used together can create a better solution to this problem. These three are: Python (Software), Raspberry Pi (Hardware), and drones (machine).

Python is an object oriented programming (OOP) language that has gained popularity in recent years. In year 1991, Guido van Rossum designed the Python program language on the emphasis on code readability and uses its syntax that allows programmers to use few lines while coding (Geeks, n.d. ). Python is user friendly and with it being OOP allows real world situations to be coded to preform very specific actions. Not to dull the audience that are not programmers, Python has come a very long way since the 90’s and has become the most popular language in the world. Python has paved the way for other languages such as Ruby, CoffeeScript, Swift, and Julia (Geeks, n.d. ). The reason why Python is a great choice for inspection purposes is because Python has become the most popular language for Artificial Intelligence (AI) and Machine Learning (ML) (Django, 2019). Python has been developed numerous times and is open source. Programmers have developed programs that can be used by anyone called libraries. These libraries help others save time and get more innovating and creative. Since ML and AI require continuous data processing, these libraries let individuals access and transform the data that is used. Since image recognition would be a game changer in the inspection process since it can get people out of danger and save thousands of hours of data processing manually, Python already have libraries that can handle this. Finding hardware that can handle this processing and yet be lightweight has been a big problem until recently. There is a microcomputer that is built on the Python language and it is called the Raspberry Pi.

During the mid-2000’s, a British engineer named Eben Upton was working on a single board computer project on his free time. It started out as a hobby taking inspiration from the BBC Micro from Acorn Computers when he was in grade school (Fromaget, n.d. ). He was trying to create a computer that was accessible to the world in terms of price and size. During this phase, Eben discovered those young students were not being taught computer sciences due to the price of technology. Just as a reminder, the year 2006 was a big leap in technology.

Facebook just became public, Google was starting to be used everywhere, and Twitter just got its first tweet. With the internet boom, Eben goal was to find a solution to connect people across the world with 1/10^th of the price of a PC. With this the Raspberry Pi was born. Since most companies were named after fruit such as Apple, Acorn, and Apricot, Raspberry seemed like the name to go with. But where does “Pi” come from? Pi comes from the language that developed the computer, Python. Today the Raspberry Pi (RPi) has become widespread and has been used from schools to hobbies to main business as a computer. The RPi can handle FLIR and Thermal cameras, touchscreens, audio and video cards, and 4g LTE data transfer and WIFI. The RPi can fit into a soap box yet it can be stacked together and become a super computer. This device has unlimited potential when paired with the Python language. With the light weight and size and processing power, programming a drone with these can make a breakthrough when it comes to image detection and processing.

The military has been using drones since the Cold War, when the US and Russia would use unmanned drones to spy on each other. What brought this technology to light is in 1982 when Israel had used UAV’s (Unmanned Arial Vehicle) alongside manned aircraft to fight the Syrian fleet (Martinez, 2019). Today UAV’s have become commercial. They are used to fight fires, inspect pipelines and even spray farms with pesticides. So why not use this technology efficiently with one of the most dangerous jobs in the world? Today drones come in all shapes and sizes and can be used for all types of jobs but most of all; they can be built from scratch by anyone who has an itch to be creative.

The process to use these three technologies to preform dangerous inspection tasks can be completed. First, being about to access Python’s program called TensorFlow allows Machine Learning and AI to start taking place. With access to thermal and FLIR cameras at much cheaper prices than their counterparts, databases can be created from previous images. Once the machine learns what images to flag and what to consider normal, a computer program can be developed. These programs can be uploaded to RPI’s which in turn can be programed with a flight model which has flight control. This flight control is what flies the drone. It helps with wind correction, flight paths, and returning to a set point when the battery gets low. Also Python has a development programing that is allowing drones to link together. This means that drones can perform actions together in swarms and learn from each other. With these technologies, a new drone development could take human lives out of harm’s way.